eMLR - model fitting

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Last updated: 2021-06-29

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Knit directory: emlr_obs_v_XXX/

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html	2edc791	jens-daniel-mueller	2021-06-04	Build site.
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Rmd	a61014f	jens-daniel-mueller	2021-05-28	test run with cstar target variable
html	12b455a	jens-daniel-mueller	2021-05-27	Build site.
Rmd	ee13efb	jens-daniel-mueller	2021-05-27	optional source of local params fully implemented
html	8c736a6	jens-daniel-mueller	2021-05-27	Build site.
Rmd	dc8e4e1	jens-daniel-mueller	2021-05-27	optional source of local params implemented
html	25bd183	jens-daniel-mueller	2021-05-26	Build site.
Rmd	e2b3434	jens-daniel-mueller	2021-05-26	generate seperate output
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Rmd	8adf952	jens-daniel-mueller	2021-05-20	parallelisation tested, not succesful
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Rmd	a9e976a	jens-daniel-mueller	2021-03-26	included model data
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html	108d6b2	jens-daniel-mueller	2021-03-20	Build site.
Rmd	2b99ba0	jens-daniel-mueller	2021-03-20	included vif removel option
html	330dcd0	jens-daniel-mueller	2021-03-20	Build site.
Rmd	4df8990	jens-daniel-mueller	2021-03-20	added vif calculation and plots
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Rmd	7f77d91	jens-daniel-mueller	2021-02-24	removed log10 color scale
html	fec3558	jens-daniel-mueller	2021-02-24	Build site.
Rmd	9ebedac	jens-daniel-mueller	2021-02-24	latitudinal residual plots
html	4bc00ea	jens-daniel-mueller	2021-02-24	Build site.
Rmd	de11bfe	jens-daniel-mueller	2021-02-24	clean up purrr approach and residual plots
html	42eca5d	jens-daniel-mueller	2021-02-24	Build site.
Rmd	06a2f3b	jens-daniel-mueller	2021-02-24	purrr residual plots by basin
html	a1ba577	jens-daniel-mueller	2021-02-24	Build site.
Rmd	9ae7d87	jens-daniel-mueller	2021-02-24	loop residual plots by basin
html	071743d	jens-daniel-mueller	2021-02-24	Build site.
Rmd	c45672c	jens-daniel-mueller	2021-02-24	added residual plots
html	ac1a836	jens-daniel-mueller	2021-02-24	Build site.
Rmd	5f655e0	jens-daniel-mueller	2021-02-24	added plots back to after switching to map aproach
html	b03fbd3	jens-daniel-mueller	2021-02-24	Build site.
Rmd	c69736b	jens-daniel-mueller	2021-02-24	added plots back to after switching to map aproach
html	86406d5	jens-daniel-mueller	2021-02-24	Build site.
Rmd	1b3c171	jens-daniel-mueller	2021-02-24	introduced purrr::map to model fitting, rebuild all
html	3d3b4cc	jens-daniel-mueller	2021-02-23	Build site.
Rmd	cbfc388	jens-daniel-mueller	2021-02-23	introduced purrr::map to model fitting
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html	33ba23c	jens-daniel-mueller	2021-01-07	Build site.
Rmd	0ad30ba	jens-daniel-mueller	2021-01-07	removed GLODAP gamma filter, target variable mapped by eras+era
html	318609d	jens-daniel-mueller	2020-12-23	adapted more variable predictor selection
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Rmd	bef9220	jens-daniel-mueller	2020-12-23	rebuild before sensitivity test
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html	02f0ee9	jens-daniel-mueller	2020-12-18	cleaned up for copying template
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Rmd	ca65bf5	jens-daniel-mueller	2020-12-18	rebuild after final cleaning
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Rmd	7e1b1c0	jens-daniel-mueller	2020-12-18	rebuild without na predictors
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Rmd	40369db	jens-daniel-mueller	2020-12-17	model selection criterion added
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Rmd	e6ed2bc	jens-daniel-mueller	2020-12-17	plotted model results
html	f3a708f	jens-daniel-mueller	2020-12-17	Build site.
Rmd	7c8ace9	jens-daniel-mueller	2020-12-17	new MLR fitting routine, rmse corrected
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Rmd	3d5a3e2	jens-daniel-mueller	2020-12-16	new MLR fitting routine
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Rmd	d7992c4	jens-daniel-mueller	2020-12-15	eMLR target variable selection
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Rmd	923aa7f	jens-daniel-mueller	2020-12-14	rebuild with new path and auto folder creation
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Rmd	91b2b29	jens-daniel-mueller	2020-12-11	selectable basinmask, try 5
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Rmd	71c63b0	jens-daniel-mueller	2020-12-09	rerun with variable predictor assignment
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Rmd	83203db	jens-daniel-mueller	2020-12-03	calculate cant with variable inventory depth
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Rmd	17d09be	jens-daniel-mueller	2020-12-01	auto eras naming
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Rmd	0895ad6	jens-daniel-mueller	2020-11-30	rebuild with all plot output
Rmd	2842970	jens-daniel-mueller	2020-11-30	cleaned for eMLR part only
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Rmd	7a4b015	jens-daniel-mueller	2020-11-30	first rebuild on ETH server
Rmd	bc61ce3	Jens Müller	2020-11-30	Initial commit

---

1 Version ID

The results displayed on this site correspond to the Version_ID: v_XXX

2 Required data

Required are:

• cleaned and prepared GLODAPv2_2020 file

GLODAP <-
  read_csv(paste(path_version_data,
                 "GLODAPv2.2020_MLR_fitting_ready.csv",
                 sep = ""))

3 Predictor combinations

Find all possible combinations of following considered predictor variables:

• sal, temp, aou, nitrate, silicate, phosphate, phosphate_star

# the following code is a workaround to find all predictor combinations
# using the olsrr package and fit all models for one era, slab, and basin

i_basin <- unique(GLODAP$basin)[1]
i_era   <- unique(GLODAP$era)[1]

# subset one basin and era for fitting
GLODAP_basin_era <- GLODAP %>%
  filter(basin == i_basin, era == i_era,
         data_source == "obs")

i_gamma_slab <- unique(GLODAP_basin_era$gamma_slab)[3]
print(i_gamma_slab)

# subset one gamma slab
GLODAP_basin_era_slab <- GLODAP_basin_era %>%
  filter(gamma_slab == i_gamma_slab)

# fit the full linear model, i.e. all predictor combinations
lm_full <- lm(paste(
  params_local$MLR_target,
  paste(params_local$MLR_predictors, collapse = " + "),
  sep = " ~ "
),
data = GLODAP_basin_era_slab)

# fit linear models for all possible predictor combinations
# unfortunately, this functions does not provide model coefficients (yet)
lm_all <- ols_step_all_possible(lm_full)

# convert to tibble
lm_all <- as_tibble(lm_all)

# format model formula
lm_all <- lm_all %>% 
  select(n, predictors) %>% 
  mutate(model = str_replace_all(predictors, " ", " + "),
         model = paste(params_local$MLR_target, "~", model))

# remove helper objects
rm(i_gamma_slab,
   i_era,
   i_basin,
   GLODAP_basin_era,
   GLODAP_basin_era_slab,
   lm_full)

4 Apply predictor threshold

Select combinations with a total number of predictors in the range:

• Minimum: 2
  
• Maximum: 5

lm_all <- lm_all %>% 
  filter(n >= params_local$MLR_predictors_min,
         n <= params_local$MLR_predictors_max)

This results in a total number of MLR models of:

• 112

5 Fit all models

Individual linear regression models were fitted for the chosen target variable:

• cstar_tref

as a function of each predictor combination. Fitting was performed separately within each basin, era, and slab. Model diagnostics, such as the root mean squared error (RMSE), were calculated for each fitted model.

library(furrr)
library(purrr)

map(c("hello", "world"), ~.x)
future_map(c("hello", "world"), ~.x)



library(tictoc)
plan(sequential)

tic()
nothingness <- future_map(c(2, 2, 2), ~Sys.sleep(.x))
toc()

plan(multisession, workers = 3)

tic()
nothingness <- future_map(c(2, 2, 2), ~Sys.sleep(.x))
toc()


future_map_dbl(1:4, function(x){
  Sys.sleep(1)
  x^2
}, .progress = TRUE)

# prepare nested data frame

GLODAP %>%
  filter_all(any_vars(is.na(.)))

GLODAP_nested <- GLODAP %>% 
  # filter(gamma_slab %in% unique(GLODAP$gamma_slab)[c(5,6)]) %>%
  nest(data = !c(gamma_slab, era, basin, data_source))

# expand with model definitions

GLODAP_nested_lm <- expand_grid(
  GLODAP_nested,
  lm_all#[1:3,]
)

# fit models and extract tidy model output
GLODAP_nested_lm_fit <- GLODAP_nested_lm %>% 
  mutate(
    fit = map2(.x = data, .y = model, 
               ~ lm(as.formula(.y), data = .x)),
    tidied = map(fit, tidy),
    glanced = map(fit, glance),
    augmented = map(fit, augment),
    vif = map(fit, ols_vif_tol)
  )


# test parallel processing

# expand with model definitions


# test multidplyr
 
# library(parallel)
# library(multidplyr)
# 
# n_cores <- detectCores()
# system.time(
# cluster <- new_cluster(n_cores - 2)
# )
# 
# cluster
# 
# system.time(
#   GLODAP_nested_lm_part <-
#     GLODAP_nested_lm %>%
#     #group_by(gamma_slab, era, basin, data_source, model, predictors, n) %>% 
#     partition(cluster)
# )
# 
# 
# GLODAP_nested_lm
# GLODAP_nested_lm_part
# 
# system.time(cluster %>%
#               cluster_library(c("tidyverse",
#                                 "broom",
#                                 "olsrr",
#                                 "purrr")))
# 
# cluster_call(cluster, search())
# 
# system.time(
# GLODAP_nested_lm_fit <- GLODAP_nested_lm_part %>%
#   mutate(
#     fit = map2(.x = data, .y = model,
#                ~ lm(as.formula(.y), data = .x)),
#     tidied = map(fit, tidy),
#     glanced = map(fit, glance),
#     augmented = map(fit, augment),
#     vif = map(fit, ols_vif_tol)
#   )
# )
# 
# system.time(
#   # extract glanced model output (model diagnostics, such as AIC)
#   GLODAP_glanced <- GLODAP_nested_lm_fit %>%
#     select(-c(data, fit, tidied, augmented, vif))
#     # unnest(glanced) %>%
#     # rename(n_predictors = n)
# )
# 
# 
# system.time(
# GLODAP_nested_lm_fit <- GLODAP_nested_lm_fit %>%
#   collect()
# )


### test furrr

# library(furrr)
# 
# plan(multisession, workers = 10)
# 
# tic()
# GLODAP_nested_lm_fit_furrr <- GLODAP_nested_lm %>%
#   mutate(
#     fit = future_map2(.x = data, .y = model,
#                ~ lm(as.formula(.y), data = .x)),
#     tidied = future_map(fit, tidy),
#     glanced = future_map(fit, glance),
#     augmented = future_map(fit, augment),
#     vif = future_map(fit, ols_vif_tol)
#   )
# toc()
# 
# plan(sequential)

# print(object.size(GLODAP_nested), units = "MB")
# print(object.size(GLODAP_nested_lm), units = "MB")
# print(object.size(GLODAP_nested_lm_fit), units = "MB")

6 Tidy models

# extract glanced model output (model diagnostics, such as AIC)
GLODAP_glanced <- GLODAP_nested_lm_fit %>%
  select(-c(data, fit, tidied, augmented, vif)) %>%
  unnest(glanced) %>% 
  rename(n_predictors = n)

# extract tidy model output (model coefficients)
GLODAP_tidy <- GLODAP_nested_lm_fit %>%
  select(-c(data, fit, glanced, augmented, vif)) %>%
  unnest(tidied)

# extract augmented model output (fitted values and residuals)
GLODAP_augmented <- GLODAP_nested_lm_fit %>% 
  select(-c(data, fit, tidied, glanced, vif)) %>% 
  unnest(augmented) 

# print(object.size(GLODAP_augmented), units = "MB")

# extract VIC from output
GLODAP_glanced_vif <- GLODAP_nested_lm_fit %>%
  select(-c(data, fit, tidied, augmented, glanced)) %>%
  unnest(vif)

# calculte max vif per model
GLODAP_glanced_vif_max <- GLODAP_glanced_vif %>% 
  group_by(data_source, era, basin, gamma_slab, model, n) %>% 
  summarise(vif_max = max(VIF)) %>% 
  ungroup()

# calculate RMSE from augmented output
GLODAP_glanced_rmse <- GLODAP_augmented %>%
  group_by(data_source, era, basin, gamma_slab, model) %>%
  summarise(rmse = sqrt(c(crossprod(.resid)) / length(.resid))) %>%
  ungroup()

# add RMSE and vif_max to glanced output
GLODAP_glanced <- full_join(GLODAP_glanced, GLODAP_glanced_rmse)
GLODAP_glanced <- full_join(GLODAP_glanced, GLODAP_glanced_vif_max)
rm(GLODAP_glanced_rmse)
rm(GLODAP_glanced_vif_max)


# extract input data
GLODAP_data <- GLODAP_nested_lm_fit %>%
  select(-c(fit, tidied, glanced, augmented, vif)) %>%
  unnest(data)

# append input data with augmented data
GLODAP_augmented <- bind_cols(
  GLODAP_data,
  GLODAP_augmented %>% select(.fitted, .resid)
)

rm(GLODAP, GLODAP_nested, GLODAP_nested_lm, GLODAP_nested_lm_fit, lm_all,
   GLODAP_data)

7 Prepare coeffcients

Coefficients are prepared for the mapping of Cant and the chosen target variable.

7.1 VIF threshold

To avoid multicollinearity among predictors, models were excluded with a VIF above:

• 1000

After removing models affected by multicollinearity, the targeted number of MLRs (10) was undercut in following fitting units:

GLODAP_glanced_clean <- GLODAP_glanced %>% 
  filter(vif_max <= params_local$vif_max)

GLODAP_glanced_clean %>% 
  group_by(data_source, era, basin, gamma_slab) %>% 
  count() %>% 
  filter(n < params_local$MLR_number)

# A tibble: 0 x 5
# Groups:   data_source, era, basin, gamma_slab [0]
# … with 5 variables: data_source <chr>, era <chr>, basin <chr>,
#   gamma_slab <chr>, n <int>

7.2 Predictor selection

Within each basin and slab, the following number of best linear regression models was selected:

• 10

The criterion used to select the best models was:

• rmse

The criterion was summed up for two adjacent eras, and the models with lowest summed values were selected.

# calculate RMSE sum for adjacent eras
lm_all_eras <- GLODAP_glanced_clean  %>%
  select(data_source, basin, gamma_slab, model, era, AIC, BIC, rmse) %>% 
  arrange(era) %>% 
  group_by(data_source, basin, gamma_slab, model) %>% 
  mutate(eras = paste(lag(era), era, sep = " --> "),
         rmse_sum = rmse + lag(rmse),
         aic_sum = AIC + lag(AIC),
         bic_sum = BIC + lag(BIC)
         ) %>% 
  ungroup() %>% 
  select(-c(era)) %>% 
  drop_na()

# subset models with lowest summed criterion
# chose which criterion is applied

if (params_local$MLR_criterion == "aic") {
  lm_best_eras <- lm_all_eras %>%
    group_by(data_source, basin, gamma_slab, eras) %>%
    slice_min(order_by = aic_sum,
              with_ties = FALSE,
              n = params_local$MLR_number) %>%
    ungroup() %>%
    arrange(basin, gamma_slab, eras, model)
} 

if (params_local$MLR_criterion == "bic") {
  lm_best_eras <- lm_all_eras %>%
    group_by(data_source, basin, gamma_slab, eras) %>%
    slice_min(order_by = bic_sum,
              with_ties = FALSE,
              n = params_local$MLR_number) %>%
    ungroup() %>%
    arrange(basin, gamma_slab, eras, model)
}

if (params_local$MLR_criterion == "rmse") {
  lm_best_eras <- lm_all_eras %>%
    group_by(data_source, basin, gamma_slab, eras) %>%
    slice_min(order_by = rmse_sum,
              with_ties = FALSE,
              n = params_local$MLR_number) %>%
    ungroup() %>%
    arrange(basin, gamma_slab, eras, model)
}


# print table
lm_best_eras %>% 
  kable() %>%
  add_header_above() %>%
  kable_styling() %>%
  scroll_box(width = "100%", height = "400px")

data_source	basin	gamma_slab	model	AIC	BIC	rmse	eras	rmse_sum	aic_sum	bic_sum
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + aou + nitrate + phosphate + phosphate_star	5796.179	5830.085	5.2764115	2000-2009 –> 2010-2019	10.918776	10685.205	10751.672
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + aou + phosphate + phosphate_star	5942.698	5971.760	5.7111152	2000-2009 –> 2010-2019	11.353892	10829.837	10886.809
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + aou + silicate + phosphate + phosphate_star	5898.113	5932.019	5.5710432	2000-2009 –> 2010-2019	11.212593	10786.916	10853.383
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	3220.124	3250.494	4.1096043	2000-2009 –> 2010-2019	9.939348	6791.501	6852.155
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	5788.616	5822.522	5.2551825	2000-2009 –> 2010-2019	11.005018	10706.849	10773.317
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	3224.084	3254.454	4.1240040	2000-2009 –> 2010-2019	9.921788	6789.315	6849.968
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	5790.710	5824.616	5.2610532	2000-2009 –> 2010-2019	11.193196	10757.264	10823.731
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + aou + phosphate	5926.351	5955.414	5.6615667	2000-2009 –> 2010-2019	11.418593	10844.520	10901.492
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate	3242.189	3272.559	4.1904938	2000-2009 –> 2010-2019	9.764295	6763.373	6824.026
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate	5882.003	5915.909	5.5234056	2000-2009 –> 2010-2019	11.261980	10797.202	10863.669
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	3250.921	3281.291	4.2229414	2000-2009 –> 2010-2019	9.803921	6773.543	6834.196
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	5879.648	5913.555	5.5164786	2000-2009 –> 2010-2019	11.388567	10830.451	10896.918
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	3229.542	3259.913	4.1439384	2000-2009 –> 2010-2019	9.933544	6793.195	6853.849
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	5798.690	5832.596	5.2834800	2000-2009 –> 2010-2019	11.232252	10769.577	10836.044
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	3268.480	3298.851	4.2889596	2000-2009 –> 2010-2019	9.963654	6809.720	6870.374
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	3252.156	3282.526	4.2275510	2000-2009 –> 2010-2019	9.825984	6778.269	6838.922
obs	Atlantic	(-Inf,26.75]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	5879.290	5913.196	5.5154233	2000-2009 –> 2010-2019	11.409644	10835.916	10902.383
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	3298.750	3329.120	4.4051923	2000-2009 –> 2010-2019	9.957550	6815.624	6876.277
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	3295.998	3326.368	4.3944976	2000-2009 –> 2010-2019	9.945717	6812.643	6873.297
mod	Atlantic	(-Inf,26.75]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	3294.823	3325.194	4.3899392	2000-2009 –> 2010-2019	9.980078	6819.279	6879.933
mod	Atlantic	(26.75,27.5]	cstar_tref ~ aou + nitrate + silicate + phosphate + phosphate_star	8637.086	8674.371	4.1272154	2000-2009 –> 2010-2019	7.871618	15997.622	16071.316
mod	Atlantic	(26.75,27.5]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	8400.799	8438.085	3.8185739	2000-2009 –> 2010-2019	8.061295	16096.432	16170.125
mod	Atlantic	(26.75,27.5]	cstar_tref ~ sal + aou + silicate + phosphate	8428.688	8460.646	3.8563021	2000-2009 –> 2010-2019	8.110057	16129.286	16192.452
mod	Atlantic	(26.75,27.5]	cstar_tref ~ sal + aou + silicate + phosphate + phosphate_star	8414.415	8451.700	3.8357153	2000-2009 –> 2010-2019	7.733967	15882.945	15956.639
obs	Atlantic	(26.75,27.5]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	11999.693	12038.115	6.9085881	2000-2009 –> 2010-2019	13.146709	21314.098	21389.383
obs	Atlantic	(26.75,27.5]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	11996.855	12035.277	6.9031083	2000-2009 –> 2010-2019	12.907416	21201.927	21277.212
mod	Atlantic	(26.75,27.5]	cstar_tref ~ sal + temp + aou + nitrate + silicate	8602.576	8639.861	4.0806282	2000-2009 –> 2010-2019	7.870210	15995.279	16068.973
mod	Atlantic	(26.75,27.5]	cstar_tref ~ sal + temp + aou + silicate + phosphate	8430.060	8467.345	3.8555055	2000-2009 –> 2010-2019	7.823438	15946.106	16019.800
mod	Atlantic	(26.75,27.5]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	8599.979	8637.264	4.0771437	2000-2009 –> 2010-2019	8.271177	16264.656	16338.350
obs	Atlantic	(26.75,27.5]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	12131.437	12169.859	7.1678550	2000-2009 –> 2010-2019	13.213726	21356.252	21431.537
obs	Atlantic	(26.75,27.5]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	11978.924	12017.346	6.8685808	2000-2009 –> 2010-2019	12.934435	21213.183	21288.468
obs	Atlantic	(26.75,27.5]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	12129.795	12168.217	7.1645643	2000-2009 –> 2010-2019	13.223367	21360.725	21436.009
obs	Atlantic	(26.75,27.5]	cstar_tref ~ temp + aou + nitrate + phosphate_star	12012.148	12045.081	6.9365701	2000-2009 –> 2010-2019	13.013186	21249.479	21314.009
mod	Atlantic	(26.75,27.5]	cstar_tref ~ temp + aou + nitrate + silicate	8696.337	8728.296	4.2112150	2000-2009 –> 2010-2019	8.015743	16097.596	16160.762
mod	Atlantic	(26.75,27.5]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	8694.505	8731.791	4.2059107	2000-2009 –> 2010-2019	7.968968	16068.370	16142.063
obs	Atlantic	(26.75,27.5]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	11987.086	12025.508	6.8842762	2000-2009 –> 2010-2019	13.169122	21322.849	21398.134
mod	Atlantic	(26.75,27.5]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	8698.181	8735.466	4.2109995	2000-2009 –> 2010-2019	7.994434	16086.530	16160.223
obs	Atlantic	(26.75,27.5]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	11997.183	12035.605	6.9037416	2000-2009 –> 2010-2019	12.979004	21235.878	21311.163
obs	Atlantic	(26.75,27.5]	cstar_tref ~ temp + nitrate + phosphate + phosphate_star	12002.074	12035.007	6.9170577	2000-2009 –> 2010-2019	13.057311	21269.223	21333.752
obs	Atlantic	(26.75,27.5]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	11976.743	12015.165	6.8643921	2000-2009 –> 2010-2019	12.996625	21242.151	21317.436
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + aou + nitrate + phosphate	10203.916	10236.982	3.9305706	2000-2009 –> 2010-2019	8.030145	18892.149	18957.225
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + aou + nitrate + phosphate + phosphate_star	9840.357	9878.933	3.5565670	2000-2009 –> 2010-2019	7.361643	18302.028	18377.950
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	10173.847	10212.424	3.8962443	2000-2009 –> 2010-2019	7.898764	18790.622	18866.543
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	13896.067	13935.671	6.4222822	2000-2009 –> 2010-2019	14.427317	26583.478	26661.594
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + aou + phosphate + phosphate_star	10818.562	10851.628	4.6501734	2000-2009 –> 2010-2019	8.852837	19582.940	19648.016
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + aou + silicate + phosphate + phosphate_star	10795.995	10834.572	4.6190305	2000-2009 –> 2010-2019	8.807380	19551.913	19627.835
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + aou + silicate + phosphate + phosphate_star	13896.496	13936.101	6.4229338	2000-2009 –> 2010-2019	14.286673	26519.406	26597.521
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + aou + silicate + phosphate_star	13895.525	13929.471	6.4244939	2000-2009 –> 2010-2019	14.436303	26584.000	26650.956
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	14093.369	14132.973	6.7286389	2000-2009 –> 2010-2019	14.603666	26721.473	26799.589
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + silicate + phosphate + phosphate_star	14093.472	14127.418	6.7319820	2000-2009 –> 2010-2019	14.609358	26720.657	26787.613
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	9963.393	10001.970	3.6782941	2000-2009 –> 2010-2019	7.541301	18471.392	18547.313
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	10783.807	10822.384	4.6036578	2000-2009 –> 2010-2019	8.909767	19624.739	19700.661
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + aou + phosphate	10897.989	10931.055	4.7523046	2000-2009 –> 2010-2019	9.013665	19704.893	19769.969
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + aou + silicate + phosphate	10893.264	10931.840	4.7435700	2000-2009 –> 2010-2019	8.979449	19683.779	19759.701
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + aou + silicate + phosphate	13886.055	13925.659	6.4071136	2000-2009 –> 2010-2019	14.273309	26510.095	26588.211
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	13895.566	13935.170	6.4215226	2000-2009 –> 2010-2019	14.286858	26519.210	26597.326
mod	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	10174.724	10213.301	3.8971792	2000-2009 –> 2010-2019	7.900010	18791.737	18867.659
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate	14044.346	14083.950	6.6511822	2000-2009 –> 2010-2019	14.784203	26789.209	26867.325
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + silicate + phosphate	14044.904	14078.850	6.6552011	2000-2009 –> 2010-2019	14.824127	26803.721	26870.678
obs	Atlantic	(27.5,28.05]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	13887.207	13926.811	6.4088566	2000-2009 –> 2010-2019	14.272859	26510.237	26588.352
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	10136.523	10174.374	5.2185271	2000-2009 –> 2010-2019	12.467581	17908.888	17982.017
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	10104.658	10142.509	5.1683194	2000-2009 –> 2010-2019	12.418454	17877.364	17950.492
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	10104.735	10142.586	5.1684392	2000-2009 –> 2010-2019	12.406949	17873.778	17946.907
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + silicate + phosphate + phosphate_star	10155.783	10188.227	5.2522968	2000-2009 –> 2010-2019	12.508805	17928.493	17991.175
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	10175.695	10213.547	5.2809187	2000-2009 –> 2010-2019	12.500622	17938.802	18011.931
mod	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + aou + phosphate	2673.920	2701.752	1.3814807	2000-2009 –> 2010-2019	2.499152	4209.986	4263.081
mod	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + aou + phosphate_star	2703.231	2731.062	1.4082366	2000-2009 –> 2010-2019	2.546591	4257.559	4310.654
mod	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + aou + silicate + phosphate	2673.111	2705.581	1.3789434	2000-2009 –> 2010-2019	2.478950	4195.309	4257.253
mod	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	2699.730	2732.200	1.4031761	2000-2009 –> 2010-2019	2.528626	4244.703	4306.647
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	10116.829	10154.680	5.1874393	2000-2009 –> 2010-2019	12.372304	17868.898	17942.027
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	10167.834	10205.685	5.2683384	2000-2009 –> 2010-2019	12.489980	17931.554	18004.682
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + nitrate + phosphate_star	10180.102	10212.546	5.2911944	2000-2009 –> 2010-2019	12.512907	17941.844	18004.526
mod	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	2716.260	2748.730	1.4184381	2000-2009 –> 2010-2019	2.567318	4281.755	4343.700
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	10091.005	10128.856	5.1469542	2000-2009 –> 2010-2019	12.348702	17848.429	17921.558
mod	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + phosphate + phosphate_star	2694.691	2722.522	1.4003880	2000-2009 –> 2010-2019	2.534339	4245.159	4298.254
mod	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	2692.956	2725.426	1.3969695	2000-2009 –> 2010-2019	2.516096	4232.318	4294.262
obs	Atlantic	(28.05,28.1]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	10144.351	10182.202	5.2309359	2000-2009 –> 2010-2019	12.435834	17902.773	17975.902
mod	Atlantic	(28.05,28.1]	cstar_tref ~ temp + aou + phosphate	2679.791	2702.984	1.3886149	2000-2009 –> 2010-2019	2.551351	4253.227	4297.472
mod	Atlantic	(28.05,28.1]	cstar_tref ~ temp + aou + silicate + phosphate	2681.322	2709.153	1.3881889	2000-2009 –> 2010-2019	2.525384	4234.635	4287.730
mod	Atlantic	(28.05,28.1]	cstar_tref ~ temp + silicate + phosphate + phosphate_star	2702.325	2730.156	1.4074017	2000-2009 –> 2010-2019	2.567476	4275.478	4328.573
obs	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	9589.822	9627.176	5.4751618	2000-2009 –> 2010-2019	15.879351	17840.734	17913.078
mod	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + aou + phosphate	2783.673	2812.818	1.0390458	2000-2009 –> 2010-2019	2.371402	5497.798	5554.991
mod	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + aou + phosphate_star	2813.297	2842.442	1.0553560	2000-2009 –> 2010-2019	2.393507	5534.297	5591.490
mod	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + aou + silicate + phosphate	2782.453	2816.455	1.0372880	2000-2009 –> 2010-2019	2.263519	5367.101	5433.825
mod	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	2814.294	2848.297	1.0547994	2000-2009 –> 2010-2019	2.293180	5414.560	5481.284
obs	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	9573.612	9610.966	5.4463287	2000-2009 –> 2010-2019	15.865983	17827.777	17900.121
obs	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	9579.057	9616.411	5.4559965	2000-2009 –> 2010-2019	15.856329	17829.157	17901.501
mod	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	2841.195	2875.198	1.0698240	2000-2009 –> 2010-2019	2.382744	5534.044	5600.768
obs	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	9559.276	9596.630	5.4209540	2000-2009 –> 2010-2019	15.845288	17814.424	17886.768
mod	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + phosphate + phosphate_star	2803.377	2832.522	1.0498659	2000-2009 –> 2010-2019	2.383998	5519.613	5576.806
mod	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	2803.277	2837.280	1.0487073	2000-2009 –> 2010-2019	2.277820	5391.642	5458.367
obs	Atlantic	(28.1,28.15]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	9579.746	9617.100	5.4572211	2000-2009 –> 2010-2019	15.874941	17833.505	17905.848
obs	Atlantic	(28.1,28.15]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	9561.727	9599.081	5.4252842	2000-2009 –> 2010-2019	15.828730	17812.483	17884.826
mod	Atlantic	(28.1,28.15]	cstar_tref ~ temp + aou + silicate + phosphate	2807.642	2836.787	1.0522227	2000-2009 –> 2010-2019	2.322999	5446.812	5504.004
mod	Atlantic	(28.1,28.15]	cstar_tref ~ temp + aou + silicate + phosphate_star	2843.433	2872.578	1.0722104	2000-2009 –> 2010-2019	2.358436	5501.744	5558.936
obs	Atlantic	(28.1,28.15]	cstar_tref ~ temp + aou + silicate + phosphate_star	9574.708	9606.726	5.4518230	2000-2009 –> 2010-2019	15.871875	17826.956	17888.965
obs	Atlantic	(28.1,28.15]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	9557.934	9595.288	5.4185852	2000-2009 –> 2010-2019	15.818751	17807.999	17880.343
obs	Atlantic	(28.1,28.15]	cstar_tref ~ temp + nitrate + silicate + phosphate_star	9560.132	9592.149	5.4259990	2000-2009 –> 2010-2019	15.851377	17813.499	17875.508
mod	Atlantic	(28.1,28.15]	cstar_tref ~ temp + silicate + phosphate + phosphate_star	2831.063	2860.208	1.0652595	2000-2009 –> 2010-2019	2.340137	5475.335	5532.528
obs	Atlantic	(28.1,28.15]	cstar_tref ~ temp + silicate + phosphate + phosphate_star	9580.735	9612.753	5.4625363	2000-2009 –> 2010-2019	15.880774	17832.602	17894.611
mod	Atlantic	(28.15,28.2]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	4435.060	4473.121	0.8895006	2000-2009 –> 2010-2019	1.912077	8311.646	8386.110
mod	Atlantic	(28.15,28.2]	cstar_tref ~ sal + temp + aou + nitrate	4329.525	4362.148	0.8627912	2000-2009 –> 2010-2019	1.849708	8108.987	8172.813
mod	Atlantic	(28.15,28.2]	cstar_tref ~ sal + temp + aou + nitrate + silicate	4230.358	4268.418	0.8374677	2000-2009 –> 2010-2019	1.819768	7999.252	8073.716
obs	Atlantic	(28.15,28.2]	cstar_tref ~ sal + temp + aou + silicate + phosphate	3689.254	3720.352	4.5141609	2000-2009 –> 2010-2019	12.618240	7137.312	7197.756
obs	Atlantic	(28.15,28.2]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	3667.510	3698.608	4.4366839	2000-2009 –> 2010-2019	12.488900	7109.289	7169.733
mod	Atlantic	(28.15,28.2]	cstar_tref ~ sal + temp + nitrate + phosphate_star	4402.376	4434.999	0.8814997	2000-2009 –> 2010-2019	1.907153	8285.015	8348.841
mod	Atlantic	(28.15,28.2]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	4394.087	4432.147	0.8788331	2000-2009 –> 2010-2019	1.880208	8214.523	8288.987
obs	Atlantic	(28.15,28.2]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	3676.725	3707.823	4.4693549	2000-2009 –> 2010-2019	12.672643	7136.683	7197.127
obs	Atlantic	(28.15,28.2]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	3674.623	3705.720	4.4618786	2000-2009 –> 2010-2019	12.526406	7117.895	7178.339
mod	Atlantic	(28.15,28.2]	cstar_tref ~ temp + aou + nitrate + phosphate	4261.476	4294.099	0.8456746	2000-2009 –> 2010-2019	1.828356	8029.412	8093.237
mod	Atlantic	(28.15,28.2]	cstar_tref ~ temp + aou + nitrate + phosphate_star	4282.848	4315.471	0.8510136	2000-2009 –> 2010-2019	1.839629	8066.918	8130.744
mod	Atlantic	(28.15,28.2]	cstar_tref ~ temp + aou + nitrate + silicate	4230.978	4263.601	0.8381141	2000-2009 –> 2010-2019	1.837168	8043.195	8107.021
obs	Atlantic	(28.15,28.2]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	3680.128	3711.225	4.4814782	2000-2009 –> 2010-2019	12.697933	7141.653	7202.098
obs	Atlantic	(28.15,28.2]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	3663.428	3694.525	4.4222858	2000-2009 –> 2010-2019	12.555480	7114.992	7175.437
obs	Atlantic	(28.15,28.2]	cstar_tref ~ temp + aou + silicate + phosphate	3688.609	3715.264	4.5190326	2000-2009 –> 2010-2019	12.798128	7155.563	7207.372
obs	Atlantic	(28.15,28.2]	cstar_tref ~ temp + aou + silicate + phosphate_star	3668.323	3694.978	4.4466303	2000-2009 –> 2010-2019	12.659622	7127.436	7179.246
mod	Atlantic	(28.15,28.2]	cstar_tref ~ temp + nitrate + phosphate + phosphate_star	4309.912	4342.535	0.8578227	2000-2009 –> 2010-2019	1.852847	8111.298	8175.124
obs	Atlantic	(28.15,28.2]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	3667.278	3698.375	4.4358618	2000-2009 –> 2010-2019	12.606845	7123.376	7183.820
mod	Atlantic	(28.15,28.2]	cstar_tref ~ temp + nitrate + silicate + phosphate_star	4415.605	4448.228	0.8849403	2000-2009 –> 2010-2019	1.886687	8235.037	8298.863
obs	Atlantic	(28.15,28.2]	cstar_tref ~ temp + silicate + phosphate + phosphate_star	3675.043	3701.698	4.4704861	2000-2009 –> 2010-2019	12.707451	7137.007	7188.817
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + aou + nitrate	3452.806	3480.480	0.6069034	2000-2009 –> 2010-2019	1.204640	5513.833	5566.674
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + aou + nitrate + phosphate	3380.160	3413.368	0.5949230	2000-2009 –> 2010-2019	1.187131	5422.112	5485.522
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + aou + nitrate + phosphate + phosphate_star	3109.851	3140.488	3.3655369	2000-2009 –> 2010-2019	7.057423	5870.727	5930.922
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + aou + nitrate + phosphate_star	3328.476	3361.684	0.5867669	2000-2009 –> 2010-2019	1.180837	5377.551	5440.961
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + aou + nitrate + silicate	3421.727	3454.936	0.6015650	2000-2009 –> 2010-2019	1.197721	5478.751	5542.160
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	3113.082	3143.719	3.3747978	2000-2009 –> 2010-2019	7.066138	5873.810	5934.005
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	2889.652	2928.395	0.5215922	2000-2009 –> 2010-2019	1.091025	4844.661	4918.638
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + aou + phosphate + phosphate_star	3110.407	3136.667	3.3728611	2000-2009 –> 2010-2019	7.065698	5869.543	5921.139
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + aou + silicate + phosphate + phosphate_star	3103.722	3134.359	3.3480444	2000-2009 –> 2010-2019	7.036990	5863.796	5923.991
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + aou + nitrate	3371.741	3404.950	0.5935869	2000-2009 –> 2010-2019	1.190414	5431.316	5494.726
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	3326.698	3365.441	0.5861751	2000-2009 –> 2010-2019	1.177439	5367.034	5441.012
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	3109.122	3139.759	3.3634522	2000-2009 –> 2010-2019	7.061004	5871.544	5931.739
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	3324.120	3362.863	0.5857716	2000-2009 –> 2010-2019	1.176069	5360.743	5434.720
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + aou + nitrate + silicate	3315.227	3353.970	0.5843819	2000-2009 –> 2010-2019	1.175107	5353.496	5427.474
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + aou + phosphate	3110.687	3136.947	3.3736632	2000-2009 –> 2010-2019	7.072045	5871.335	5922.931
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + aou + silicate + phosphate	3101.471	3132.108	3.3416408	2000-2009 –> 2010-2019	7.035885	5862.991	5923.186
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	3118.318	3148.955	3.3898558	2000-2009 –> 2010-2019	7.015224	5860.867	5921.062
mod	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	3345.756	3384.500	0.5891665	2000-2009 –> 2010-2019	1.186890	5410.735	5484.713
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	3121.786	3152.423	3.3998679	2000-2009 –> 2010-2019	7.050312	5871.284	5931.479
obs	Atlantic	(28.2, Inf]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	3108.257	3138.895	3.3609807	2000-2009 –> 2010-2019	7.001780	5855.088	5915.284
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + aou + silicate + phosphate + phosphate_star	11425.970	11464.486	5.6409920	2000-2009 –> 2010-2019	10.913857	25935.405	26014.261
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + aou + silicate + phosphate + phosphate_star	14033.271	14073.132	5.8888636	2000-2009 –> 2010-2019	12.081268	32307.690	32389.153
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	11311.518	11350.033	5.4656234	2000-2009 –> 2010-2019	11.013319	26059.957	26138.813
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	14089.442	14129.302	5.9646619	2000-2009 –> 2010-2019	12.175239	32380.365	32461.827
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	11460.135	11498.651	5.6944235	2000-2009 –> 2010-2019	11.468390	26396.624	26475.481
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	14112.982	14152.842	5.9967168	2000-2009 –> 2010-2019	12.237089	32430.860	32512.322
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + aou + phosphate	11484.630	11517.643	5.7362074	2000-2009 –> 2010-2019	11.633319	26518.389	26585.981
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + aou + silicate + phosphate	11081.621	11120.137	5.1296674	2000-2009 –> 2010-2019	10.398227	25587.213	25666.070
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + aou + silicate + phosphate	14064.361	14104.222	5.9306975	2000-2009 –> 2010-2019	12.122779	32338.487	32419.949
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	11246.707	11285.222	5.3687452	2000-2009 –> 2010-2019	10.900553	25981.654	26060.511
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	14113.986	14153.847	5.9980880	2000-2009 –> 2010-2019	12.236792	32430.358	32511.820
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	11481.995	11520.510	5.7288750	2000-2009 –> 2010-2019	11.544569	26452.357	26531.213
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	14115.827	14155.688	6.0006031	2000-2009 –> 2010-2019	12.244826	32437.180	32518.642
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + nitrate + phosphate_star	14130.044	14164.211	6.0228011	2000-2009 –> 2010-2019	12.287961	32468.250	32538.074
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	11460.116	11498.631	5.6943926	2000-2009 –> 2010-2019	11.539531	26454.234	26533.090
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	14041.095	14080.956	5.8993637	2000-2009 –> 2010-2019	12.110102	32332.164	32413.626
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	11279.462	11317.977	5.4174905	2000-2009 –> 2010-2019	10.996046	26053.995	26132.852
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	14111.758	14151.618	5.9950459	2000-2009 –> 2010-2019	12.233089	32427.534	32508.996
mod	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + silicate + phosphate_star	11460.318	11493.331	5.6978535	2000-2009 –> 2010-2019	11.543017	26452.456	26520.047
obs	Indo-Pacific	(-Inf,26.5]	cstar_tref ~ sal + temp + silicate + phosphate_star	14120.965	14155.131	6.0103632	2000-2009 –> 2010-2019	12.249835	32436.030	32505.855
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ aou + nitrate + phosphate + phosphate_star	11074.923	11107.768	5.5865951	2000-2009 –> 2010-2019	10.950473	23772.697	23839.287
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ aou + nitrate + silicate + phosphate + phosphate_star	8859.770	8897.785	3.3294506	2000-2009 –> 2010-2019	7.382975	18817.528	18893.870
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ aou + silicate + phosphate + phosphate_star	9130.483	9163.067	3.6097367	2000-2009 –> 2010-2019	7.954702	19331.193	19396.629
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	9212.043	9250.058	3.6958677	2000-2009 –> 2010-2019	7.932353	19325.552	19401.894
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	10961.000	10999.320	5.4058122	2000-2009 –> 2010-2019	10.411411	23377.755	23455.444
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	10976.364	11014.683	5.4294312	2000-2009 –> 2010-2019	10.496461	23443.056	23520.744
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate	8990.763	9028.778	3.4612555	2000-2009 –> 2010-2019	7.558881	18986.696	19063.039
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	9125.382	9163.397	3.6021479	2000-2009 –> 2010-2019	7.814629	19218.843	19295.186
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	10978.324	11016.644	5.4324527	2000-2009 –> 2010-2019	10.509539	23453.134	23530.822
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ sal + temp + nitrate + phosphate_star	11007.008	11039.854	5.4799604	2000-2009 –> 2010-2019	10.684864	23581.610	23648.200
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	11008.175	11046.495	5.4786650	2000-2009 –> 2010-2019	10.622155	23536.184	23613.872
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	9141.834	9179.849	3.6197558	2000-2009 –> 2010-2019	7.842076	19243.527	19319.869
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ temp + aou + nitrate + phosphate	11093.934	11126.779	5.6168140	2000-2009 –> 2010-2019	11.044212	23839.905	23906.495
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	8919.923	8957.938	3.3893413	2000-2009 –> 2010-2019	7.537751	18959.313	19035.655
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	11079.366	11117.686	5.5904697	2000-2009 –> 2010-2019	11.003942	23816.819	23894.508
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	9154.951	9192.966	3.6338556	2000-2009 –> 2010-2019	7.882720	19278.753	19355.096
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	11112.769	11151.089	5.6437117	2000-2009 –> 2010-2019	11.107606	23888.178	23965.866
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ temp + aou + silicate + phosphate	9234.264	9266.849	3.7224949	2000-2009 –> 2010-2019	8.208315	19547.530	19612.967
mod	Indo-Pacific	(26.5,26.75]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	9203.622	9241.637	3.6866543	2000-2009 –> 2010-2019	7.953840	19342.604	19418.947
obs	Indo-Pacific	(26.5,26.75]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	11116.151	11154.470	5.6491301	2000-2009 –> 2010-2019	11.116951	23894.501	23972.189
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ aou + nitrate + phosphate + phosphate_star	10384.415	10417.883	3.4344367	2000-2009 –> 2010-2019	7.024262	22743.473	22811.357
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ aou + nitrate + phosphate + phosphate_star	14950.749	14985.570	5.1091381	2000-2009 –> 2010-2019	10.176312	32136.311	32206.805
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ aou + nitrate + silicate + phosphate + phosphate_star	10074.124	10113.171	3.1707979	2000-2009 –> 2010-2019	6.712330	22373.178	22452.376
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ aou + phosphate + phosphate_star	15151.539	15180.556	5.3251097	2000-2009 –> 2010-2019	10.579243	32539.665	32598.410
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	9971.012	10010.059	3.0882724	2000-2009 –> 2010-2019	6.424692	21996.937	22076.135
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	15061.980	15102.604	5.2243574	2000-2009 –> 2010-2019	10.387202	32355.147	32437.390
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	10110.003	10149.050	3.2000277	2000-2009 –> 2010-2019	6.651305	22290.875	22370.073
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ sal + temp + aou + silicate + phosphate	15159.485	15200.109	5.3294013	2000-2009 –> 2010-2019	10.578870	32546.596	32628.839
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	10125.003	10164.050	3.2123270	2000-2009 –> 2010-2019	6.672707	22317.934	22397.132
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ sal + temp + nitrate + phosphate_star	10409.534	10443.003	3.4565723	2000-2009 –> 2010-2019	7.007918	22719.256	22787.141
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	10308.119	10347.166	3.3663476	2000-2009 –> 2010-2019	6.902531	22600.253	22679.451
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	15099.415	15140.039	5.2644392	2000-2009 –> 2010-2019	10.428531	32393.945	32476.188
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ temp + aou + nitrate + phosphate	15104.607	15139.428	5.2721758	2000-2009 –> 2010-2019	10.502928	32469.553	32540.047
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	10050.788	10089.835	3.1519301	2000-2009 –> 2010-2019	6.702638	22361.688	22440.887
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	15048.156	15088.780	5.2096330	2000-2009 –> 2010-2019	10.362889	32330.826	32413.069
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	10185.469	10224.516	3.2623901	2000-2009 –> 2010-2019	6.949398	22668.814	22748.012
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	15129.586	15170.210	5.2969680	2000-2009 –> 2010-2019	10.536395	32505.887	32588.130
mod	Indo-Pacific	(26.75,27]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	10205.179	10244.226	3.2788775	2000-2009 –> 2010-2019	6.980296	22706.382	22785.580
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	15124.874	15165.498	5.2918746	2000-2009 –> 2010-2019	10.531292	32501.165	32583.408
obs	Indo-Pacific	(26.75,27]	cstar_tref ~ temp + nitrate + silicate + phosphate_star	15131.473	15166.294	5.3011736	2000-2009 –> 2010-2019	10.540807	32505.996	32576.490
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ aou + nitrate + phosphate + phosphate_star	11201.366	11235.720	2.8577370	2000-2009 –> 2010-2019	5.870275	25148.399	25218.298
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ aou + nitrate + silicate + phosphate + phosphate_star	11167.844	11207.924	2.8354254	2000-2009 –> 2010-2019	5.760692	24954.427	25035.976
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	15918.122	15959.234	4.9991327	2000-2009 –> 2010-2019	9.699428	36389.547	36473.678
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	15995.366	16036.479	5.0732011	2000-2009 –> 2010-2019	9.907845	36661.134	36745.266
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + aou + silicate + phosphate	15919.594	15954.834	5.0024389	2000-2009 –> 2010-2019	9.703413	36390.015	36462.128
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + aou + silicate + phosphate_star	15996.581	16031.820	5.0763072	2000-2009 –> 2010-2019	9.927768	36684.295	36756.408
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	15965.839	16006.951	5.0447589	2000-2009 –> 2010-2019	9.832572	36564.483	36648.615
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + silicate + phosphate + phosphate_star	15966.098	16001.337	5.0469295	2000-2009 –> 2010-2019	9.855510	36592.590	36664.702
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	11180.105	11220.185	2.8431069	2000-2009 –> 2010-2019	5.852798	25123.912	25205.461
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	11374.123	11414.204	2.9674656	2000-2009 –> 2010-2019	6.083907	25510.536	25592.085
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + temp + aou + silicate + phosphate	15910.316	15951.428	4.9917076	2000-2009 –> 2010-2019	9.682702	36368.080	36452.211
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	15991.170	16032.282	5.0691490	2000-2009 –> 2010-2019	9.821459	36538.487	36622.619
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	11386.559	11426.640	2.9756197	2000-2009 –> 2010-2019	6.100820	25538.482	25620.031
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	16084.154	16125.267	5.1596956	2000-2009 –> 2010-2019	9.935651	36665.699	36749.830
obs	Indo-Pacific	(27,27.25]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	15967.745	16008.857	5.0465900	2000-2009 –> 2010-2019	9.788692	36500.234	36584.366
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ temp + aou + nitrate + phosphate	11364.848	11399.203	2.9627061	2000-2009 –> 2010-2019	6.040807	25430.855	25500.754
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ temp + aou + nitrate + phosphate_star	11535.576	11569.930	3.0764446	2000-2009 –> 2010-2019	6.248736	25768.144	25838.043
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	11359.867	11399.948	2.9581458	2000-2009 –> 2010-2019	5.990111	25344.422	25425.971
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	11537.318	11577.399	3.0762698	2000-2009 –> 2010-2019	6.222194	25725.764	25807.313
mod	Indo-Pacific	(27,27.25]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	11545.666	11585.746	3.0819413	2000-2009 –> 2010-2019	6.233326	25743.694	25825.243
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	13327.929	13368.720	3.4395946	2000-2009 –> 2010-2019	6.442932	30327.791	30411.445
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	15482.259	15523.607	4.1731830	2000-2009 –> 2010-2019	8.331046	36439.032	36523.859
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	13542.507	13583.297	3.5899280	2000-2009 –> 2010-2019	6.788715	30967.559	31051.213
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	15644.053	15685.402	4.2993530	2000-2009 –> 2010-2019	8.655116	36943.241	37028.068
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + aou + silicate + phosphate	15487.399	15522.841	4.1786723	2000-2009 –> 2010-2019	8.347032	36460.739	36533.448
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	13466.141	13506.931	3.5356871	2000-2009 –> 2010-2019	6.671152	30756.354	30840.008
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	15570.940	15612.288	4.2418720	2000-2009 –> 2010-2019	8.499705	36702.674	36787.500
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + silicate + phosphate + phosphate_star	15569.006	15604.447	4.2419235	2000-2009 –> 2010-2019	8.540418	36768.731	36841.440
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	13561.493	13602.283	3.6035420	2000-2009 –> 2010-2019	6.714895	30799.642	30883.296
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + temp + aou + silicate + phosphate	15489.343	15530.691	4.1786288	2000-2009 –> 2010-2019	8.284753	36353.906	36438.733
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	15593.125	15634.473	4.2592321	2000-2009 –> 2010-2019	8.417317	36550.290	36635.117
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	13449.414	13490.204	3.5239162	2000-2009 –> 2010-2019	6.521251	30435.783	30519.436
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	15606.212	15647.560	4.2695057	2000-2009 –> 2010-2019	8.432748	36572.505	36657.331
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	15557.071	15598.420	4.2310561	2000-2009 –> 2010-2019	8.379831	36497.731	36582.558
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ temp + aou + nitrate + phosphate	13576.902	13611.865	3.6160705	2000-2009 –> 2010-2019	6.770842	30906.514	30978.217
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	13341.573	13382.364	3.4489632	2000-2009 –> 2010-2019	6.486059	30416.815	30500.468
obs	Indo-Pacific	(27.25,27.5]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	15691.870	15733.219	4.3373665	2000-2009 –> 2010-2019	8.624112	36873.441	36958.268
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	13455.035	13495.825	3.5278675	2000-2009 –> 2010-2019	6.649822	30716.126	30799.780
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	13447.357	13488.148	3.5224720	2000-2009 –> 2010-2019	6.644099	30707.740	30791.394
mod	Indo-Pacific	(27.25,27.5]	cstar_tref ~ temp + nitrate + silicate + phosphate_star	13493.508	13528.471	3.5564483	2000-2009 –> 2010-2019	6.678413	30752.621	30824.324
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ aou + silicate + phosphate + phosphate_star	16992.084	17028.110	4.1236836	2000-2009 –> 2010-2019	7.675741	36986.014	37059.368
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	14753.107	14794.484	3.6092548	2000-2009 –> 2010-2019	6.388743	32592.789	32677.585
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	16734.743	16776.773	3.9488985	2000-2009 –> 2010-2019	7.628590	36993.249	37078.828
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	14811.122	14852.499	3.6478522	2000-2009 –> 2010-2019	6.459316	32734.327	32819.123
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + aou + silicate + phosphate	16751.195	16787.222	3.9610861	2000-2009 –> 2010-2019	7.702451	37131.333	37204.687
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + aou + silicate + phosphate_star	14914.292	14949.758	3.7188763	2000-2009 –> 2010-2019	6.646683	33131.582	33204.264
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	14796.736	14838.113	3.6382427	2000-2009 –> 2010-2019	6.438945	32691.937	32776.733
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + silicate + phosphate + phosphate_star	14915.149	14950.614	3.7194605	2000-2009 –> 2010-2019	6.651466	33142.902	33215.584
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate	14879.075	14920.452	3.6935862	2000-2009 –> 2010-2019	6.601233	33047.912	33132.708
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate	16692.112	16734.143	3.9208849	2000-2009 –> 2010-2019	7.346234	36417.868	36503.447
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	14904.491	14945.868	3.7108385	2000-2009 –> 2010-2019	6.633444	33110.797	33195.593
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	16716.633	16758.664	3.9369740	2000-2009 –> 2010-2019	7.396744	36516.760	36602.339
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate	14900.634	14942.011	3.7082153	2000-2009 –> 2010-2019	6.652442	33160.760	33245.556
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	14812.322	14853.698	3.6486543	2000-2009 –> 2010-2019	6.479523	32785.754	32870.550
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	16752.211	16794.242	3.9604350	2000-2009 –> 2010-2019	7.417660	36546.863	36632.442
mod	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	14891.921	14933.298	3.7022958	2000-2009 –> 2010-2019	6.618240	33081.564	33166.360
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	16710.879	16752.909	3.9331921	2000-2009 –> 2010-2019	7.390890	36506.549	36592.128
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ sal + temp + silicate + phosphate_star	16925.733	16961.759	4.0782427	2000-2009 –> 2010-2019	7.554390	36758.985	36832.339
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	16963.264	17005.295	4.1025138	2000-2009 –> 2010-2019	7.700857	37055.491	37141.070
obs	Indo-Pacific	(27.5,27.75]	cstar_tref ~ temp + aou + silicate + phosphate	16986.200	17022.226	4.1196334	2000-2009 –> 2010-2019	7.721005	37082.684	37156.037
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ aou + nitrate + silicate + phosphate + phosphate_star	21162.286	21206.126	3.7004888	2000-2009 –> 2010-2019	6.499372	43092.205	43180.891
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	12135.498	12176.261	2.7382035	2000-2009 –> 2010-2019	4.956274	26262.719	26345.946
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	12084.000	12124.763	2.7101234	2000-2009 –> 2010-2019	4.938658	26241.201	26324.428
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	12144.831	12185.594	2.7433235	2000-2009 –> 2010-2019	4.981654	26329.970	26413.196
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	11971.946	12012.708	2.6500153	2000-2009 –> 2010-2019	4.926820	26265.650	26348.876
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	11980.438	12021.200	2.6545235	2000-2009 –> 2010-2019	4.936161	26287.648	26370.874
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + aou + nitrate + silicate	11992.993	12033.756	2.6612029	2000-2009 –> 2010-2019	4.897659	26172.797	26256.023
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + aou + silicate + phosphate	12075.165	12115.928	2.7053353	2000-2009 –> 2010-2019	4.960913	26309.199	26392.426
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + aou + silicate + phosphate	21207.958	21251.798	3.7223493	2000-2009 –> 2010-2019	6.522476	43141.855	43230.540
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	12086.665	12127.428	2.7115697	2000-2009 –> 2010-2019	4.973278	26337.989	26421.215
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	21192.036	21235.875	3.7147135	2000-2009 –> 2010-2019	6.525962	43161.416	43250.101
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	12000.013	12040.776	2.6649448	2000-2009 –> 2010-2019	4.950877	26319.200	26402.426
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	21147.946	21191.786	3.6936515	2000-2009 –> 2010-2019	6.511440	43138.129	43226.814
mod	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	12095.913	12136.676	2.7165935	2000-2009 –> 2010-2019	4.978779	26348.583	26431.809
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	21191.419	21235.258	3.7144179	2000-2009 –> 2010-2019	6.527055	43165.220	43253.905
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	21137.197	21181.036	3.6885345	2000-2009 –> 2010-2019	6.493470	43086.452	43175.138
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	21141.174	21185.014	3.6904271	2000-2009 –> 2010-2019	6.508714	43132.941	43221.627
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ temp + aou + silicate + phosphate	21231.429	21269.006	3.7345970	2000-2009 –> 2010-2019	6.542492	43188.127	43264.143
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	21140.153	21183.993	3.6899411	2000-2009 –> 2010-2019	6.509759	43136.781	43225.466
obs	Indo-Pacific	(27.75,27.95]	cstar_tref ~ temp + nitrate + silicate + phosphate_star	21152.525	21190.102	3.6967866	2000-2009 –> 2010-2019	6.526025	43177.009	43253.025
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ aou + nitrate + phosphate + phosphate_star	23079.548	23117.612	3.7581726	2000-2009 –> 2010-2019	6.711669	47615.449	47692.497
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ aou + nitrate + silicate + phosphate + phosphate_star	23069.954	23114.362	3.7529950	2000-2009 –> 2010-2019	6.684600	47534.932	47624.820
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ aou + phosphate + phosphate_star	23241.812	23273.532	3.8322985	2000-2009 –> 2010-2019	6.789886	47789.281	47853.488
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ aou + silicate + phosphate + phosphate_star	23226.094	23264.159	3.8242336	2000-2009 –> 2010-2019	6.769144	47733.459	47810.507
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + aou + nitrate + phosphate + phosphate_star	23078.032	23122.441	3.7566018	2000-2009 –> 2010-2019	6.710006	47615.627	47705.515
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	8894.326	8933.937	1.9669151	2000-2009 –> 2010-2019	3.882459	18268.211	18347.890
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + aou + phosphate + phosphate_star	23237.188	23275.252	3.8292814	2000-2009 –> 2010-2019	6.786074	47784.022	47861.070
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + aou + nitrate	8959.971	8993.923	1.9985619	2000-2009 –> 2010-2019	3.786992	18021.224	18089.520
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	8823.625	8863.236	1.9343740	2000-2009 –> 2010-2019	3.722591	17886.337	17966.016
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	23146.018	23190.426	3.7870930	2000-2009 –> 2010-2019	6.789106	47843.627	47933.516
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + aou + nitrate + silicate	8917.596	8957.207	1.9777447	2000-2009 –> 2010-2019	3.719994	17862.496	17942.175
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + aou + phosphate	9075.043	9108.995	2.0535714	2000-2009 –> 2010-2019	3.920679	18331.065	18399.361
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + aou + phosphate_star	9075.835	9109.787	2.0539548	2000-2009 –> 2010-2019	3.925105	18341.641	18409.937
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + aou + silicate + phosphate	9076.412	9116.023	2.0532656	2000-2009 –> 2010-2019	3.888680	18256.981	18336.660
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	9077.359	9116.970	2.0537245	2000-2009 –> 2010-2019	3.894818	18271.904	18351.583
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	8821.916	8861.527	1.9335941	2000-2009 –> 2010-2019	3.724340	17891.021	17970.700
mod	Indo-Pacific	(27.95,28.05]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	9079.870	9119.481	2.0549416	2000-2009 –> 2010-2019	3.897490	18277.990	18357.669
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ temp + aou + nitrate + phosphate	23149.819	23187.883	3.7897060	2000-2009 –> 2010-2019	6.792483	47847.920	47924.967
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	23148.995	23193.403	3.7884338	2000-2009 –> 2010-2019	6.731796	47653.206	47743.094
obs	Indo-Pacific	(27.95,28.05]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	23215.450	23259.858	3.8184880	2000-2009 –> 2010-2019	6.784813	47795.832	47885.721
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ aou + nitrate + phosphate + phosphate_star	17635.157	17672.340	2.7396357	2000-2009 –> 2010-2019	5.505425	35319.819	35394.179
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ aou + phosphate + phosphate_star	17715.283	17746.269	2.7707943	2000-2009 –> 2010-2019	5.537186	35399.525	35461.492
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ aou + silicate + phosphate + phosphate_star	17697.018	17734.201	2.7630730	2000-2009 –> 2010-2019	5.527384	35377.804	35452.164
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	17715.971	17759.352	2.7695308	2000-2009 –> 2010-2019	5.543797	35424.833	35511.587
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	17644.438	17687.819	2.7423841	2000-2009 –> 2010-2019	5.537212	35406.865	35493.619
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + aou + nitrate + silicate	6246.719	6284.217	1.7679202	2000-2009 –> 2010-2019	3.525299	12756.246	12831.553
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + aou + silicate + phosphate	6331.862	6369.360	1.8166087	2000-2009 –> 2010-2019	3.461578	12624.841	12700.148
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + aou + silicate + phosphate	17691.726	17735.107	2.7603000	2000-2009 –> 2010-2019	5.507171	35328.602	35415.356
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	6334.878	6372.377	1.8183580	2000-2009 –> 2010-2019	3.468166	12637.479	12712.786
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	17757.278	17800.658	2.7853290	2000-2009 –> 2010-2019	5.557831	35461.526	35548.280
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	6317.051	6354.549	1.8080439	2000-2009 –> 2010-2019	3.457706	12619.363	12694.670
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	17708.865	17752.246	2.7668223	2000-2009 –> 2010-2019	5.534452	35400.354	35487.108
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	6334.680	6372.179	1.8182431	2000-2009 –> 2010-2019	3.468074	12637.328	12712.635
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	17761.520	17804.901	2.7869568	2000-2009 –> 2010-2019	5.558970	35464.488	35551.242
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ sal + temp + silicate + phosphate_star	6333.824	6365.965	1.8189068	2000-2009 –> 2010-2019	3.468749	12634.494	12699.042
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	6528.563	6566.061	1.9342797	2000-2009 –> 2010-2019	3.592194	12847.221	12922.528
obs	Indo-Pacific	(28.05,28.1]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	17715.707	17759.088	2.7694302	2000-2009 –> 2010-2019	5.533647	35398.244	35484.998
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate_star	6531.606	6569.105	1.9361591	2000-2009 –> 2010-2019	3.602424	12866.724	12942.031
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ temp + aou + silicate + phosphate	6528.497	6560.639	1.9354739	2000-2009 –> 2010-2019	3.603123	12864.334	12928.883
mod	Indo-Pacific	(28.05,28.1]	cstar_tref ~ temp + nitrate + silicate + phosphate_star	6529.825	6561.966	1.9362940	2000-2009 –> 2010-2019	3.609419	12876.402	12940.951
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + aou + nitrate + phosphate + phosphate_star	15765.012	15807.881	2.4956387	2000-2009 –> 2010-2019	5.040328	31628.462	31714.186
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	10769.795	10811.750	1.4868977	2000-2009 –> 2010-2019	2.989987	22049.407	22133.600
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	15766.494	15809.363	2.4961867	2000-2009 –> 2010-2019	5.029371	31599.421	31685.144
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + aou + phosphate + phosphate_star	15797.023	15833.768	2.5082451	2000-2009 –> 2010-2019	5.057617	31670.859	31744.337
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + aou + silicate + phosphate	15800.768	15837.513	2.5096371	2000-2009 –> 2010-2019	5.046168	31640.589	31714.066
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + nitrate + silicate + phosphate	10838.131	10874.093	1.5046570	2000-2009 –> 2010-2019	3.058733	22321.500	22393.665
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	10837.494	10879.450	1.5039875	2000-2009 –> 2010-2019	3.032174	22219.244	22303.438
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	15847.850	15890.719	2.5264546	2000-2009 –> 2010-2019	5.086565	31751.999	31837.723
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	15838.372	15881.241	2.5229095	2000-2009 –> 2010-2019	5.100770	31789.063	31874.787
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + aou + nitrate + silicate	10301.297	10343.252	1.3738365	2000-2009 –> 2010-2019	3.042189	22224.317	22308.510
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + aou + silicate + phosphate	10143.336	10185.292	1.3376879	2000-2009 –> 2010-2019	2.786939	21197.965	21282.159
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + aou + silicate + phosphate	15772.766	15815.635	2.4985073	2000-2009 –> 2010-2019	5.024029	31585.288	31671.011
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	10157.001	10198.956	1.3407770	2000-2009 –> 2010-2019	2.792970	21224.139	21308.333
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	15833.544	15876.413	2.5211058	2000-2009 –> 2010-2019	5.062182	31687.425	31773.149
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate	10619.094	10661.049	1.4495496	2000-2009 –> 2010-2019	2.999606	22088.486	22172.680
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	10115.606	10157.561	1.3314407	2000-2009 –> 2010-2019	2.781716	21174.592	21258.785
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	15868.436	15911.305	2.5341716	2000-2009 –> 2010-2019	5.092273	31767.298	31853.021
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	10154.602	10196.557	1.3402342	2000-2009 –> 2010-2019	2.792380	21221.539	21305.732
obs	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	15825.035	15867.904	2.5179299	2000-2009 –> 2010-2019	5.055676	31670.082	31755.805
mod	Indo-Pacific	(28.1,28.2]	cstar_tref ~ sal + temp + silicate + phosphate_star	10232.194	10268.155	1.3583624	2000-2009 –> 2010-2019	2.810804	21298.386	21370.552
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ aou + nitrate + phosphate + phosphate_star	5367.676	5398.599	1.9635578	2000-2009 –> 2010-2019	4.624706	9637.985	9697.641
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ aou + nitrate + silicate + phosphate + phosphate_star	5322.247	5358.324	1.9274862	2000-2009 –> 2010-2019	4.588436	9594.423	9664.023
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ aou + silicate + phosphate + phosphate_star	5380.807	5411.730	1.9736633	2000-2009 –> 2010-2019	4.643270	9656.752	9716.408
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + aou + nitrate + phosphate + phosphate_star	5345.764	5381.841	1.9452883	2000-2009 –> 2010-2019	4.601253	9614.610	9684.210
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	12908.097	12954.277	0.7956725	2000-2009 –> 2010-2019	1.466319	25202.099	25295.202
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate	5352.223	5388.299	1.9502060	2000-2009 –> 2010-2019	4.643481	9645.843	9715.443
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	13966.413	14012.593	0.8773363	2000-2009 –> 2010-2019	1.678415	28401.187	28494.290
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + aou + silicate + phosphate + phosphate_star	5381.140	5417.217	1.9723775	2000-2009 –> 2010-2019	4.632235	9652.586	9722.186
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + nitrate + silicate + phosphate	13068.719	13108.302	0.8077081	2000-2009 –> 2010-2019	1.629704	27811.996	27891.799
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	12998.862	13045.042	0.8023677	2000-2009 –> 2010-2019	1.487415	25548.786	25641.889
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + temp + aou + phosphate + phosphate_star	5380.500	5416.577	1.9718841	2000-2009 –> 2010-2019	4.619385	9643.677	9713.277
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + temp + aou + silicate + phosphate	13763.844	13810.024	0.8610816	2000-2009 –> 2010-2019	1.734503	29240.110	29333.213
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	13770.075	13816.254	0.8615771	2000-2009 –> 2010-2019	1.735329	29250.893	29343.996
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate	13037.698	13083.878	0.8052496	2000-2009 –> 2010-2019	1.606052	27468.320	27561.423
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate_star	14108.901	14155.081	0.8889533	2000-2009 –> 2010-2019	1.770851	29701.496	29794.599
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	13768.792	13814.972	0.8614751	2000-2009 –> 2010-2019	1.735206	29249.328	29342.431
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ temp + aou + nitrate + phosphate + phosphate_star	5348.238	5384.315	1.9471708	2000-2009 –> 2010-2019	4.600518	9615.333	9684.932
mod	Indo-Pacific	(28.2,28.3]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	14604.267	14650.446	0.9305505	2000-2009 –> 2010-2019	1.779218	29734.201	29827.304
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ temp + aou + phosphate + phosphate_star	5389.489	5420.412	1.9803732	2000-2009 –> 2010-2019	4.644720	9661.930	9721.587
obs	Indo-Pacific	(28.2,28.3]	cstar_tref ~ temp + aou + silicate + phosphate + phosphate_star	5377.287	5413.363	1.9694087	2000-2009 –> 2010-2019	4.629469	9648.869	9718.469
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ aou + nitrate + phosphate + phosphate_star	10202.393	10238.767	1.2054576	2000-2009 –> 2010-2019	2.043104	17322.338	17394.468
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ aou + nitrate + silicate + phosphate + phosphate_star	10198.050	10240.487	1.2042534	2000-2009 –> 2010-2019	2.040478	17310.272	17394.424
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + aou + nitrate + phosphate + phosphate_star	10136.033	10178.470	1.1925420	2000-2009 –> 2010-2019	2.027917	17242.435	17326.587
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + aou + nitrate + silicate + phosphate_star	1710.956	1738.701	2.1430696	2000-2009 –> 2010-2019	4.927123	2980.579	3033.168
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + aou + silicate + phosphate + phosphate_star	1701.736	1729.481	2.1178206	2000-2009 –> 2010-2019	4.872590	2965.924	3018.512
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + aou + silicate + phosphate_star	1708.971	1732.752	2.1431097	2000-2009 –> 2010-2019	4.928241	2976.793	3021.869
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + nitrate + silicate + phosphate + phosphate_star	1723.345	1751.090	2.1774686	2000-2009 –> 2010-2019	4.936005	2988.235	3040.824
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + silicate + phosphate + phosphate_star	1721.792	1745.574	2.1787201	2000-2009 –> 2010-2019	4.937594	2984.745	3029.821
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + temp + aou + nitrate + phosphate	10121.187	10163.624	1.1897553	2000-2009 –> 2010-2019	2.022912	17212.368	17296.520
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + temp + aou + nitrate + phosphate_star	10158.918	10201.355	1.1968503	2000-2009 –> 2010-2019	2.032962	17270.368	17354.520
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + temp + aou + silicate + phosphate	1723.066	1750.811	2.1766889	2000-2009 –> 2010-2019	4.930830	2987.137	3039.726
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + temp + aou + silicate + phosphate_star	1708.794	1736.539	2.1371219	2000-2009 –> 2010-2019	4.922071	2978.583	3031.171
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + temp + nitrate + phosphate + phosphate_star	10122.849	10165.286	1.1900670	2000-2009 –> 2010-2019	2.024484	17222.686	17306.838
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + temp + nitrate + silicate + phosphate	1725.988	1753.733	2.1848780	2000-2009 –> 2010-2019	4.947356	2991.612	3044.201
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + temp + silicate + phosphate	1724.039	1747.820	2.1850210	2000-2009 –> 2010-2019	4.947539	2987.670	3032.746
obs	Indo-Pacific	(28.3,28.4]	cstar_tref ~ sal + temp + silicate + phosphate + phosphate_star	1720.031	1747.776	2.1682130	2000-2009 –> 2010-2019	4.924585	2984.518	3037.106
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ temp + aou + nitrate + phosphate	10188.253	10224.627	1.2027746	2000-2009 –> 2010-2019	2.038205	17293.035	17365.166
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ temp + aou + nitrate + silicate + phosphate	10185.042	10227.479	1.2017874	2000-2009 –> 2010-2019	2.035599	17280.722	17364.874
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ temp + nitrate + phosphate + phosphate_star	10191.488	10227.862	1.2033879	2000-2009 –> 2010-2019	2.040049	17304.695	17376.825
mod	Indo-Pacific	(28.3,28.4]	cstar_tref ~ temp + nitrate + silicate + phosphate + phosphate_star	10188.100	10230.537	1.2023667	2000-2009 –> 2010-2019	2.037491	17292.781	17376.933
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ sal + temp + aou + phosphate	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.656889	-Inf	-Inf
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ sal + temp + nitrate + phosphate_star	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.652663	-Inf	-Inf
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ sal + temp + silicate + phosphate	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.519547	-Inf	-Inf
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ sal + temp + silicate + phosphate_star	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.538645	-Inf	-Inf
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ temp + aou + silicate + phosphate	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.581647	-Inf	-Inf
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ temp + aou + silicate + phosphate_star	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.545706	-Inf	-Inf
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ temp + nitrate + phosphate + phosphate_star	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.853069	-Inf	-Inf
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ temp + nitrate + silicate + phosphate	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.567579	-Inf	-Inf
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ temp + nitrate + silicate + phosphate_star	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.674364	-Inf	-Inf
obs	Indo-Pacific	(28.4, Inf]	cstar_tref ~ temp + silicate + phosphate + phosphate_star	-Inf	-Inf	0.0000000	2000-2009 –> 2010-2019	1.565887	-Inf	-Inf

7.3 Target variable coefficients

A data frame to map the target variable is prepared.

# create table with two era belonging to one eras
eras_forward <- GLODAP_glanced %>%
  arrange(era) %>% 
  group_by(basin, gamma_slab, model) %>% 
  mutate(eras = paste(era, lead(era), sep = " --> ")) %>% 
  ungroup() %>% 
  select(era, eras) %>% 
  unique()

eras_backward <- GLODAP_glanced %>%
  arrange(era) %>% 
  group_by(basin, gamma_slab, model) %>% 
  mutate(eras = paste(lag(era), era, sep = " --> ")) %>% 
  ungroup() %>% 
  select(era, eras) %>% 
  unique()

eras_era <- full_join(eras_backward, eras_forward) %>% 
  filter(str_detect(eras, "NA") == FALSE)

# extend best model selection from eras to era
lm_best <- full_join(
  lm_best_eras %>% select(data_source, basin, gamma_slab, model, eras),
  eras_era) %>% 
  drop_na() %>% 
  arrange(era, basin, gamma_slab, data_source)

lm_best <- left_join(
  lm_best,
  GLODAP_tidy %>% select(data_source, basin, gamma_slab, era, model, term, estimate))

rm(eras_era, eras_forward, eras_backward)

7.4 Cant coeffcients

A data frame of coefficient offsets is prepared to facilitate the direct mapping of Cant.

# subtract coefficients of adjacent era  
lm_best_cant <- lm_best %>%
  arrange(era) %>%
  group_by(data_source, basin, gamma_slab, eras, model, term) %>%
  mutate(delta_coeff = estimate - lag(estimate)) %>%
  ungroup() %>%
  arrange(basin, gamma_slab, model, term, eras) %>%
  drop_na() %>%
  select(-c(era,estimate))

# pivot to wide format
lm_best_cant <- lm_best_cant %>%
  pivot_wider(values_from = delta_coeff,
              names_from = term,
              names_prefix = "delta_coeff_",
              values_fill = 0)

# create table of target variable coefficients in wide format
lm_best_target <- lm_best %>% 
  pivot_wider(names_from = "term",
              names_prefix = "coeff_",
              values_from = "estimate",
              values_fill = 0
              )

GLODAP_augmented_best <- left_join(
  lm_best_target %>% select(data_source, basin, gamma_slab, era, model),
  GLODAP_augmented
)

7.5 Write files

lm_best_target %>%
  write_csv(paste(path_version_data,
                  "lm_best_target.csv",
                  sep = ""))

lm_best_cant %>%
  write_csv(paste(path_version_data,
                  "lm_best_cant.csv",
                  sep = ""))

GLODAP_augmented_best %>%
  write_csv(paste(path_version_data,
                  "lm_residuals_best_models.csv",
                  sep = ""))

8 Model diagnotics

8.1 Selection criterion vs predictors

The selection criterion (rmse) was plotted against the number of predictors (limited to 2 - 5).

8.1.1 All models

GLODAP_glanced %>%
  group_split(era) %>%
  map(
    ~ ggplot(data = .x,
             aes(
               as.factor(n_predictors),
               !!sym(params_local$MLR_criterion),
               col = data_source
             )) +
      geom_hline(yintercept = c(0, 10)) +
      geom_boxplot() +
      facet_grid(gamma_slab ~ basin) +
      scale_color_brewer(palette = "Set1") +
      ylim(c(0, NA)) +
      labs(x = "Number of predictors",
           title = paste("Era:", unique(.x$era)))
  )

[[1]]

Past versions of eMLR_predictor_model_quality_all-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
ac1a836	jens-daniel-mueller	2021-02-24
b03fbd3	jens-daniel-mueller	2021-02-24
3d3b4cc	jens-daniel-mueller	2021-02-23
7b672f7	jens-daniel-mueller	2021-01-11
33ba23c	jens-daniel-mueller	2021-01-07
318609d	jens-daniel-mueller	2020-12-23
9d0b2d0	jens-daniel-mueller	2020-12-23
0aa2b50	jens-daniel-mueller	2020-12-23
2886da0	jens-daniel-mueller	2020-12-19
02f0ee9	jens-daniel-mueller	2020-12-18
7bcb4eb	jens-daniel-mueller	2020-12-18
7131186	jens-daniel-mueller	2020-12-17
5b48ef5	jens-daniel-mueller	2020-12-17
f3a708f	jens-daniel-mueller	2020-12-17

[[2]]

Past versions of eMLR_predictor_model_quality_all-2.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26

8.1.2 Best models

left_join(lm_best_target %>% select(basin, gamma_slab, era, model),
          GLODAP_glanced) %>%
  group_split(era) %>%
  imap(
  ~ ggplot(data = .x,
         aes("",
             !!sym(params_local$MLR_criterion),
             col = data_source)) +
  geom_hline(yintercept = c(0, 10)) +
  geom_boxplot() +
  facet_grid(gamma_slab ~ basin) +
  scale_color_brewer(palette = "Set1") +
  ylim(c(0, NA)) +
  labs(x = "Number of predictors pooled",
           title = paste("Era:", unique(.x$era)))
  )

[[1]]

Past versions of eMLR_predictor_model_quality_best-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
c6b3da6	jens-daniel-mueller	2021-06-14
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
ac1a836	jens-daniel-mueller	2021-02-24
b03fbd3	jens-daniel-mueller	2021-02-24
3d3b4cc	jens-daniel-mueller	2021-02-23
7b672f7	jens-daniel-mueller	2021-01-11
33ba23c	jens-daniel-mueller	2021-01-07
318609d	jens-daniel-mueller	2020-12-23
9d0b2d0	jens-daniel-mueller	2020-12-23
0aa2b50	jens-daniel-mueller	2020-12-23
2886da0	jens-daniel-mueller	2020-12-19
02f0ee9	jens-daniel-mueller	2020-12-18
7bcb4eb	jens-daniel-mueller	2020-12-18
7131186	jens-daniel-mueller	2020-12-17
5b48ef5	jens-daniel-mueller	2020-12-17
f3a708f	jens-daniel-mueller	2020-12-17

[[2]]

Past versions of eMLR_predictor_model_quality_best-2.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26

8.2 RMSE correlation between eras

RMSE was plotted to compare the agreement for one model applied to two adjecent eras (ie check whether the same predictor combination performs equal in both eras).

8.2.1 All models

# find max rmse to scale axis
max_rmse <-
  max(c(lm_all_eras$rmse,
        lm_all_eras$rmse_sum - lm_all_eras$rmse))

lm_all_eras %>%
  ggplot(aes(rmse, rmse_sum - rmse, col = gamma_slab)) +
  geom_point() +
  scale_color_viridis_d() +
  coord_equal(xlim = c(0, max_rmse),
              ylim = c(0, max_rmse)) +
  geom_abline(slope = 1,
              col = 'red') +
  facet_grid(data_source ~ basin)

Past versions of rmse_correlation_across_eras_all_models-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
ac1a836	jens-daniel-mueller	2021-02-24
b03fbd3	jens-daniel-mueller	2021-02-24
3d3b4cc	jens-daniel-mueller	2021-02-23
7b672f7	jens-daniel-mueller	2021-01-11
33ba23c	jens-daniel-mueller	2021-01-07
318609d	jens-daniel-mueller	2020-12-23
9d0b2d0	jens-daniel-mueller	2020-12-23
0aa2b50	jens-daniel-mueller	2020-12-23
2886da0	jens-daniel-mueller	2020-12-19
02f0ee9	jens-daniel-mueller	2020-12-18
7bcb4eb	jens-daniel-mueller	2020-12-18
7131186	jens-daniel-mueller	2020-12-17
5b48ef5	jens-daniel-mueller	2020-12-17
e4ca289	jens-daniel-mueller	2020-12-16
158fe26	jens-daniel-mueller	2020-12-15
7a9a4cb	jens-daniel-mueller	2020-12-15
61b263c	jens-daniel-mueller	2020-12-15
984697e	jens-daniel-mueller	2020-12-12
3ebff89	jens-daniel-mueller	2020-12-12
ba112d3	jens-daniel-mueller	2020-12-11
24a632f	jens-daniel-mueller	2020-12-07
6a8004b	jens-daniel-mueller	2020-12-07
70bf1a5	jens-daniel-mueller	2020-12-07
7555355	jens-daniel-mueller	2020-12-07
143d6fa	jens-daniel-mueller	2020-12-07
090e4d5	jens-daniel-mueller	2020-12-02
7c25f7a	jens-daniel-mueller	2020-12-02
b03ddb8	jens-daniel-mueller	2020-12-02
91435ae	jens-daniel-mueller	2020-12-01
196be51	jens-daniel-mueller	2020-11-30

rm(max_rmse)

8.2.2 Best models

# find max rmse to scale axis
max_rmse <-
  max(c(lm_best_eras$rmse,
        lm_best_eras$rmse_sum - lm_best_eras$rmse))

lm_best_eras %>%
  ggplot(aes(rmse, rmse_sum - rmse, col = gamma_slab)) +
  geom_point() +
  scale_color_viridis_d() +
  coord_equal(xlim = c(0, max_rmse),
              ylim = c(0, max_rmse)) +
  geom_abline(slope = 1,
              col = 'red') +
  facet_grid(data_source ~ basin)

Past versions of rmse_correlation_across_eras_best_models-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
ac1a836	jens-daniel-mueller	2021-02-24
b03fbd3	jens-daniel-mueller	2021-02-24
3d3b4cc	jens-daniel-mueller	2021-02-23
7b672f7	jens-daniel-mueller	2021-01-11
33ba23c	jens-daniel-mueller	2021-01-07
318609d	jens-daniel-mueller	2020-12-23
9d0b2d0	jens-daniel-mueller	2020-12-23
0aa2b50	jens-daniel-mueller	2020-12-23
2886da0	jens-daniel-mueller	2020-12-19
02f0ee9	jens-daniel-mueller	2020-12-18
7bcb4eb	jens-daniel-mueller	2020-12-18
7131186	jens-daniel-mueller	2020-12-17
a84ff3c	jens-daniel-mueller	2020-12-17

rm(max_rmse)

8.3 Predictor counts

The number of models where a particular predictor was included were counted for each basin, density slab and compared eras

# calculate cases of predictor used
lm_all_stats <- lm_best_cant %>% 
  pivot_longer(starts_with("delta_coeff_"),
               names_to = "term",
               names_prefix = "delta_coeff_",
               values_to = "delta_coeff") %>% 
  filter(term != "(Intercept)",
         delta_coeff != 0) %>% 
  group_by(data_source, basin, gamma_slab) %>% 
  count(term) %>% 
  ungroup() %>% 
  pivot_wider(values_from = n, names_from = term)

# print table
lm_all_stats %>%
  gt(rowname_col = "gamma_slab",
     groupname_col = c("basin", "data_source")) %>% 
  summary_rows(
    groups = TRUE,
    fns = list(total = "sum")
  )

	aou	nitrate	phosphate	phosphate_star	sal	silicate	temp
Atlantic - mod
(-Inf,26.75]	6	7	6	7	7	7	10
(26.75,27.5]	10	6	6	4	6	10	6
(27.5,28.05]	9	6	9	5	10	3	5
(28.05,28.1]	6	1	7	6	7	6	10
(28.1,28.15]	6	1	6	7	7	7	10
(28.15,28.2]	6	10	2	6	5	5	9
(28.2, Inf]	9	10	3	4	10	3	5
total	52.00	41.00	39.00	39.00	52.00	41.00	55.00
Indo-Pacific - mod
(-Inf,26.5]	6	4	6	7	10	6	9
(26.5,26.75]	8	5	8	6	4	9	8
(26.75,27]	6	10	6	8	5	5	8
(27,27.25]	8	10	7	7	3	4	8
(27.25,27.5]	6	10	6	6	5	8	7
(27.5,27.75]	5	5	6	7	10	10	5
(27.75,27.95]	7	7	6	6	10	7	7
(27.95,28.05]	8	5	5	5	10	5	9
(28.05,28.1]	6	5	4	6	6	10	10
(28.1,28.2]	4	6	6	5	10	10	7
(28.2,28.3]	5	7	7	5	9	10	6
(28.3,28.4]	7	10	9	7	4	3	7
total	76.00	84.00	76.00	75.00	86.00	87.00	91.00
Atlantic - obs
(-Inf,26.75]	8	4	8	7	10	4	7
(26.75,27.5]	6	8	6	8	5	5	10
(27.5,28.05]	5	3	7	7	10	10	5
(28.05,28.1]	4	7	5	9	10	7	6
(28.1,28.15]	4	6	4	10	5	8	10
(28.15,28.2]	6	4	6	7	4	10	10
(28.2, Inf]	8	4	9	6	10	5	6
total	41.00	36.00	45.00	54.00	54.00	49.00	54.00
Indo-Pacific - obs
(-Inf,26.5]	5	5	5	8	10	6	9
(26.5,26.75]	6	10	6	7	5	4	9
(26.75,27]	7	8	7	6	3	6	8
(27,27.25]	6	4	6	7	10	10	4
(27.25,27.5]	6	5	7	6	9	10	5
(27.5,27.75]	7	3	7	5	7	10	7
(27.75,27.95]	6	6	6	7	4	10	9
(27.95,28.05]	9	7	10	7	3	4	4
(28.05,28.1]	8	5	8	6	6	7	6
(28.1,28.2]	7	5	8	6	10	7	5
(28.2,28.3]	10	5	10	9	4	5	4
(28.3,28.4]	5	3	7	7	10	10	5
(28.4, Inf]	3	4	6	6	4	7	10
total	85.00	70.00	93.00	87.00	85.00	96.00	85.00

8.4 RMSE alternatives

8.4.1 AIC

AIC is an alternative criterion to RMSE to judge model quality, but not (yet) taken into account.

lm_all_eras %>% 
  ggplot(aes(rmse, AIC, col = gamma_slab)) +
  geom_point() +
  scale_color_viridis_d() +
  facet_grid(data_source~basin)

Past versions of aic_vs_rmse_all_models-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
ac1a836	jens-daniel-mueller	2021-02-24
b03fbd3	jens-daniel-mueller	2021-02-24
3d3b4cc	jens-daniel-mueller	2021-02-23
7b672f7	jens-daniel-mueller	2021-01-11
33ba23c	jens-daniel-mueller	2021-01-07
318609d	jens-daniel-mueller	2020-12-23
9d0b2d0	jens-daniel-mueller	2020-12-23
0aa2b50	jens-daniel-mueller	2020-12-23
2886da0	jens-daniel-mueller	2020-12-19
02f0ee9	jens-daniel-mueller	2020-12-18
7bcb4eb	jens-daniel-mueller	2020-12-18
7131186	jens-daniel-mueller	2020-12-17
5b48ef5	jens-daniel-mueller	2020-12-17

lm_best_eras %>% 
  ggplot(aes(rmse, AIC, col = gamma_slab)) +
  geom_point() +
  scale_color_viridis_d() +
  facet_grid(data_source~basin)

Past versions of aic_vs_rmse_selected_models-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
ac1a836	jens-daniel-mueller	2021-02-24
b03fbd3	jens-daniel-mueller	2021-02-24
3d3b4cc	jens-daniel-mueller	2021-02-23
7b672f7	jens-daniel-mueller	2021-01-11
33ba23c	jens-daniel-mueller	2021-01-07
318609d	jens-daniel-mueller	2020-12-23
9d0b2d0	jens-daniel-mueller	2020-12-23
0aa2b50	jens-daniel-mueller	2020-12-23
2886da0	jens-daniel-mueller	2020-12-19
02f0ee9	jens-daniel-mueller	2020-12-18
7bcb4eb	jens-daniel-mueller	2020-12-18
7131186	jens-daniel-mueller	2020-12-17
5b48ef5	jens-daniel-mueller	2020-12-17

8.4.2 AIC vs BIC

BIC is an alternative criterion to RMSE to judge model quality, but not (yet) taken into account.

lm_all_eras %>% 
  ggplot(aes(AIC, BIC, col = gamma_slab)) +
  geom_point() +
  scale_color_viridis_d() +
  facet_grid(data_source~basin)

Past versions of BIC_vs_AIC_all_models-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20

8.5 RMSE vs VIF

GLODAP_glanced %>% 
  ggplot(aes(rmse, log10(vif_max),col=data_source)) +
  geom_hline(yintercept = 1) +
  geom_point() +
  scale_color_brewer(palette = "Set1") +
  facet_grid(gamma_slab~basin)

Past versions of rmse_vs_VIF_all_models-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20

8.6 Residual patterns

8.6.1 Fitted vs true

Plotted are fitted vs actual target variable values, here: rparams_local$MLR_target`

# calculate equal axis limits and binwidth
axis_lims <- GLODAP_augmented %>%
  summarise(
    max_value = max(
      c(max(.fitted, max(!!sym(params_local$MLR_target))))
      ),
    min_value = min(
      c(min(.fitted, min(!!sym(params_local$MLR_target))))
    )
  )

i_binwidth <- 5
# binwidth_value <- (axis_lims$max_value - axis_lims$min_value) / 40
axis_lims <- c(axis_lims$min_value, axis_lims$max_value)

GLODAP_augmented %>%
  ggplot(aes(!!sym(params_local$MLR_target), .fitted)) +
  geom_bin2d(binwidth = i_binwidth) +
  scale_fill_viridis_c(trans = "log10") +
  geom_abline(slope = 1,
              col = "black") +
  coord_equal(xlim = axis_lims,
              ylim = axis_lims) +
  labs(title = "All models") +
  facet_wrap(~data_source)

Past versions of fitted_vs_actual_all-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
27ae473	jens-daniel-mueller	2021-02-24
4bc00ea	jens-daniel-mueller	2021-02-24

GLODAP_augmented %>%
  ggplot(aes(!!sym(params_local$MLR_target) - .fitted)) +
  geom_histogram(binwidth = i_binwidth) +
  labs(title = "All models") +
  scale_x_continuous(limits = c(-50,50)) +
  facet_wrap(~data_source)

GLODAP_augmented_best %>%
  ggplot(aes(!!sym(params_local$MLR_target), .fitted)) +
  geom_bin2d(binwidth = i_binwidth) +
  scale_fill_viridis_c(trans = "log10") +
  geom_abline(slope = 1,
              col = "black") +
  coord_equal(xlim = axis_lims,
              ylim = axis_lims) +
  labs(title = "Selected models") +
  facet_wrap(~data_source)

Past versions of fitted_vs_actual_best-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
27ae473	jens-daniel-mueller	2021-02-24
4bc00ea	jens-daniel-mueller	2021-02-24

GLODAP_augmented_best %>%
  ggplot(aes(!!sym(params_local$MLR_target) - .fitted)) +
  geom_histogram(binwidth = i_binwidth) +
  labs(title = "Selected models") +
    scale_x_continuous(limits = c(-50,50)) +
  facet_wrap(~data_source)

rm(binwidth_value, axis_lims)

8.6.2 Pooled

In the following, we present residual patterns vs latitude across all domains.

i_ylim <- c(-30,30)

GLODAP_augmented_best %>%
  ggplot(aes(lat, .resid)) +
  geom_bin2d(binwidth = i_binwidth) +
  geom_hline(yintercept = 0, col = "black") +
  scale_fill_viridis_c(trans = "log10") +
  labs(
    title = paste(
      "Target variable:",
      params_local$MLR_target,
      "| Selected models",
      "| All domains"
    )
  ) +
  facet_wrap(~data_source)

Past versions of residual_patterns_full_range-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
27ae473	jens-daniel-mueller	2021-02-24
4bc00ea	jens-daniel-mueller	2021-02-24

Due to the few large residuals, we limit the y axis range for the plots below.

GLODAP_augmented_best %>%
  ggplot(aes(lat, .resid)) +
  geom_bin2d(binwidth = i_binwidth) +
  geom_hline(yintercept = 0, col = "black") +
  scale_fill_viridis_c(trans = "log10") +
  coord_cartesian(ylim = i_ylim) +
  labs(
    title = paste(
      "Target variable:",
      params_local$MLR_target,
      "| Selected models",
      "| All domains"
    )
  ) +
  facet_wrap(~data_source)

Past versions of residual_patterns_y_range_limit-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
27ae473	jens-daniel-mueller	2021-02-24
4bc00ea	jens-daniel-mueller	2021-02-24

8.6.3 By model domain

In the following, we present residual patterns vs latitude for separate model domains, ie basins, density slabs and eras.

GLODAP_augmented_best %>% 
  group_split(basin, data_source) %>% 
  # head(1) %>% 
  map(~ ggplot(data = .x, aes(lat, .resid)) +
      geom_bin2d(binwidth = i_binwidth) +
      geom_hline(yintercept = 0, col = "black") +
      scale_fill_viridis_c(trans = "log10") +
      facet_grid(gamma_slab ~ era) +
      coord_cartesian(ylim = i_ylim) +
      labs(
        title = paste(
          "Target:",
          params_local$MLR_target,
          "| best models | basin:",
          unique(.x$basin),
          "| data_source:",
          unique(.x$data_source)
        )
      ))

[[1]]

Past versions of residual_patterns_by_model_domain-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
c6b3da6	jens-daniel-mueller	2021-06-14
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
27ae473	jens-daniel-mueller	2021-02-24
a1ba577	jens-daniel-mueller	2021-02-24
071743d	jens-daniel-mueller	2021-02-24

[[2]]

Past versions of residual_patterns_by_model_domain-2.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
27ae473	jens-daniel-mueller	2021-02-24
a1ba577	jens-daniel-mueller	2021-02-24

[[3]]

Past versions of residual_patterns_by_model_domain-3.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
c6b3da6	jens-daniel-mueller	2021-06-14
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26

[[4]]

Past versions of residual_patterns_by_model_domain-4.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26

8.6.4 Latitudinal mean

GLODAP_augmented_best <- GLODAP_augmented_best %>%
  mutate(lat_grid = as.numeric(as.character(cut(
    lat,
    seq(-90, 90, 10),
    seq(-85, 85, 10)
  ))))

lat_residual <- GLODAP_augmented_best %>%
  group_by(data_source, basin, gamma_slab, era, lat_grid) %>% 
  summarise(.resid_mean = mean(.resid)) %>% 
  ungroup()

lat_residual %>%
  group_split(basin) %>% 
  map(
  ~ggplot(data = .x,
          aes(lat_grid, .resid_mean, col=era)) +
  geom_line() +
  geom_point() +
  geom_hline(yintercept = 0, col = "black") +
  facet_grid(gamma_slab ~ data_source) +
    labs(title = paste("Basin:", unique(.x$basin)))
  )

[[1]]

Past versions of latitudinal_residual-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
fec3558	jens-daniel-mueller	2021-02-24

[[2]]

Past versions of latitudinal_residual-2.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26

8.6.5 Latitudinal offset

# calculate residual offset for adjacent eras
lat_residual_offset <- lat_residual  %>%
  select(data_source, basin, gamma_slab, era, lat_grid, .resid_mean) %>% 
  arrange(era) %>% 
  group_by(data_source, basin, gamma_slab, lat_grid) %>% 
  mutate(.resid_mean_offset = .resid_mean - lag(.resid_mean)) %>% 
  ungroup() %>% 
  drop_na()

lat_residual_offset %>%
  ggplot(aes(lat_grid, .resid_mean_offset, col=data_source)) +
  geom_line() +
  geom_point() +
  geom_hline(yintercept = 0, col = "black") +
  facet_grid(gamma_slab ~ basin)

Past versions of latitudinal_residual_offset-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
3b6387f	jens-daniel-mueller	2021-06-18
c6b3da6	jens-daniel-mueller	2021-06-14
439ee80	jens-daniel-mueller	2021-06-11
33ffcab	jens-daniel-mueller	2021-06-10
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
69c79d0	jens-daniel-mueller	2021-06-08
1772903	jens-daniel-mueller	2021-06-07
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
2edc791	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
be90356	jens-daniel-mueller	2021-06-02
d37a85d	jens-daniel-mueller	2021-05-31
4b7a5ee	jens-daniel-mueller	2021-05-28
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
a00ec94	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
06bfaf7	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
f155edd	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
83a13de	jens-daniel-mueller	2021-03-20
cf98c6d	jens-daniel-mueller	2021-03-16
a1d52ff	jens-daniel-mueller	2021-03-15
0bade3b	jens-daniel-mueller	2021-03-15
27c1f4b	jens-daniel-mueller	2021-03-14
af75ebf	jens-daniel-mueller	2021-03-14
5017709	jens-daniel-mueller	2021-03-11
585b07f	jens-daniel-mueller	2021-03-11
85a5ed2	jens-daniel-mueller	2021-03-10
6c0bec6	jens-daniel-mueller	2021-03-05
3c2ec33	jens-daniel-mueller	2021-03-05
af70b94	jens-daniel-mueller	2021-03-04
fec3558	jens-daniel-mueller	2021-02-24

8.6.6 Spatial mean

GLODAP_augmented_best <- GLODAP_augmented_best %>%
  mutate(lon_grid = as.numeric(as.character(cut(
    lon,
    seq(-360, 500, 10),
    seq(-355, 500, 10)
  ))))

spatial_residual <- GLODAP_augmented_best %>%
  group_by(data_source, gamma_slab, era, lat_grid, lon_grid) %>% 
  summarise(.resid_mean = mean(.resid)) %>% 
  ungroup()

spatial_obs <- GLODAP_augmented_best %>%
  distinct(gamma_slab, era, lat, lon)

spatial_residual %>%
  rename(lat = lat_grid,
         lon = lon_grid) %>%
  group_split(data_source, gamma_slab) %>%
  # head(1) %>%
  map(~ p_map_cant_slab(
    df = .x,
    var = ".resid_mean",
    col = "divergent",
    title_text = "Residual distribution",
    subtitle_text = paste(
      "Data source:",
      unique(.x$data_source),
      "| density slab:",
      unique(.x$gamma_slab)
      ),
    legend_title = paste(params_local$MLR_target, "\nbias")
  ) +
    geom_raster(data = spatial_obs,
                aes(lon, lat)) +
    facet_grid(era ~ .)
  )

[[1]]

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[[31]]

[[32]]

[[33]]

[[34]]

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[[36]]

[[37]]

8.6.7 Spatial offset

# calculate residual offset for adjacent eras
spatial_residual_offset <- spatial_residual  %>%
  select(data_source, gamma_slab, era, lat_grid, lon_grid, .resid_mean) %>% 
  arrange(era) %>% 
  group_by(data_source, gamma_slab, lat_grid, lon_grid) %>% 
  mutate(.resid_mean_offset = .resid_mean - lag(.resid_mean)) %>% 
  ungroup() %>% 
  drop_na()

spatial_obs <- spatial_obs %>% 
  count(lon, lat, gamma_slab) %>% 
  filter(n == 2) %>% 
  select(-n)

spatial_residual_offset %>%
  rename(lat = lat_grid,
         lon = lon_grid) %>%
  group_split(data_source, gamma_slab) %>%
  # head(1) %>%
  map(~ p_map_cant_slab(
    df = .x,
    var = ".resid_mean_offset",
    col = "divergent",
    title_text = "Residual offset distribution (era 2 - era 1)",
    subtitle_text = paste(
      "Data source:",
      unique(.x$data_source),
      "| density slab:",
      unique(.x$gamma_slab)
      ),
    legend_title = paste(params_local$MLR_target, "\nbias offset")
  ) +
    geom_raster(data = spatial_obs,
                aes(lon, lat))
  )

[[1]]

[[2]]

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[[4]]

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9 VIF

GLODAP_glanced %>% 
  ggplot(aes(as.factor(n),
             log10(vif_max),
             col=data_source)) + 
  geom_hline(yintercept = log10(params_local$vif_max)) +
  scale_color_brewer(palette = "Set1") +
  geom_violin() +
  facet_grid(gamma_slab~basin)

Past versions of vif_distribution_n_predictors-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
d37a85d	jens-daniel-mueller	2021-05-31
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
594d503	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
330dcd0	jens-daniel-mueller	2021-03-20

GLODAP_glanced_vif %>% 
  ggplot(aes(Variables,
             log10(VIF),
             col = data_source)) + 
  geom_hline(yintercept = log10(params_local$vif_max)) +
  geom_violin() +
  scale_color_brewer(palette = "Set1") +
  facet_grid(gamma_slab~basin) +
  coord_flip()

Past versions of vif_distribution_type_predictor-1.png

Version	Author	Date
d054c39	jens-daniel-mueller	2021-06-24
4fcd066	jens-daniel-mueller	2021-06-24
7e1f407	jens-daniel-mueller	2021-06-10
2cbe18c	jens-daniel-mueller	2021-06-10
594ed9a	jens-daniel-mueller	2021-06-04
db7df0e	jens-daniel-mueller	2021-06-04
207339d	jens-daniel-mueller	2021-06-03
315710b	jens-daniel-mueller	2021-06-03
d37a85d	jens-daniel-mueller	2021-05-31
25bd183	jens-daniel-mueller	2021-05-26
62bd574	jens-daniel-mueller	2021-05-20
7c56c39	jens-daniel-mueller	2021-05-19
52e7583	jens-daniel-mueller	2021-05-12
969e631	jens-daniel-mueller	2021-05-12
d2a83bc	jens-daniel-mueller	2021-04-16
c0a47df	jens-daniel-mueller	2021-04-16
50290e8	jens-daniel-mueller	2021-04-16
b6fe355	jens-daniel-mueller	2021-04-16
81b7c6d	jens-daniel-mueller	2021-04-16
ddec5b7	jens-daniel-mueller	2021-04-15
29edae5	jens-daniel-mueller	2021-04-14
099d566	jens-daniel-mueller	2021-04-14
bb44686	jens-daniel-mueller	2021-04-14
bf40480	jens-daniel-mueller	2021-04-13
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
d3c3fde	jens-daniel-mueller	2021-03-26
594d503	jens-daniel-mueller	2021-03-26
2eb881a	jens-daniel-mueller	2021-03-26
03b6009	jens-daniel-mueller	2021-03-23
de6256b	jens-daniel-mueller	2021-03-23
380d215	jens-daniel-mueller	2021-03-21
33b385b	jens-daniel-mueller	2021-03-20
108d6b2	jens-daniel-mueller	2021-03-20
330dcd0	jens-daniel-mueller	2021-03-20

Session information

sessionInfo()

R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.2

Matrix products: default
BLAS:   /usr/local/R-4.0.3/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.0.3/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] tictoc_1.0.1     gt_0.2.2         corrr_0.4.3      broom_0.7.5     
 [5] kableExtra_1.3.1 knitr_1.30       olsrr_0.5.3      GGally_2.0.0    
 [9] lubridate_1.7.9  metR_0.9.0       scico_1.2.0      patchwork_1.1.1 
[13] collapse_1.5.0   forcats_0.5.0    stringr_1.4.0    dplyr_1.0.5     
[17] purrr_0.3.4      readr_1.4.0      tidyr_1.1.2      tibble_3.0.4    
[21] ggplot2_3.3.3    tidyverse_1.3.0  workflowr_1.6.2 

loaded via a namespace (and not attached):
 [1] fs_1.5.0                 webshot_0.5.2            RColorBrewer_1.1-2      
 [4] httr_1.4.2               rprojroot_2.0.2          tools_4.0.3             
 [7] backports_1.1.10         utf8_1.1.4               R6_2.5.0                
[10] nortest_1.0-4            DBI_1.1.0                colorspace_1.4-1        
[13] withr_2.3.0              gridExtra_2.3            tidyselect_1.1.0        
[16] curl_4.3                 compiler_4.0.3           git2r_0.27.1            
[19] cli_2.1.0                rvest_0.3.6              xml2_1.3.2              
[22] sass_0.2.0               labeling_0.4.2           scales_1.1.1            
[25] checkmate_2.0.0          goftest_1.2-2            digest_0.6.27           
[28] foreign_0.8-80           rmarkdown_2.5            rio_0.5.16              
[31] pkgconfig_2.0.3          htmltools_0.5.0          highr_0.8               
[34] dbplyr_1.4.4             rlang_0.4.10             readxl_1.3.1            
[37] rstudioapi_0.11          farver_2.0.3             generics_0.0.2          
[40] jsonlite_1.7.1           zip_2.1.1                car_3.0-10              
[43] magrittr_1.5             Matrix_1.2-18            Rcpp_1.0.5              
[46] munsell_0.5.0            fansi_0.4.1              abind_1.4-5             
[49] lifecycle_1.0.0          stringi_1.5.3            whisker_0.4             
[52] yaml_2.2.1               carData_3.0-4            plyr_1.8.6              
[55] grid_4.0.3               blob_1.2.1               parallel_4.0.3          
[58] promises_1.1.1           crayon_1.3.4             lattice_0.20-41         
[61] haven_2.3.1              hms_0.5.3                pillar_1.4.7            
[64] reprex_0.3.0             glue_1.4.2               evaluate_0.14           
[67] RcppArmadillo_0.10.1.2.0 data.table_1.13.2        modelr_0.1.8            
[70] vctrs_0.3.5              httpuv_1.5.4             cellranger_1.1.0        
[73] gtable_0.3.0             reshape_0.8.8            assertthat_0.2.1        
[76] xfun_0.18                openxlsx_4.2.3           RcppEigen_0.3.3.7.0     
[79] later_1.1.0.1            viridisLite_0.3.0        ellipsis_0.3.1          
[82] here_0.1