elasticnet
Last updated: 2022-07-18
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Knit directory:
ampel-leipzig-meld/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | 9da49ce | Sebastian Gibb | 2022-06-19 | chore: rebuild site |
| Rmd | ac8a09d | Sebastian Gibb | 2022-06-19 | feat: use plot(…, what = "path") introduced in ameld 0.0.25 |
| html | fb43d01 | Sebastian Gibb | 2022-06-19 | chore: rebuild site |
| html | ebe29cf | Sebastian Gibb | 2022-06-16 | chore: rebuild site |
| html | 8035219 | Sebastian Gibb | 2022-06-15 | chore: rebuild site |
| Rmd | 7ffaeb9 | Sebastian Gibb | 2022-06-15 | feat: add analysis of complete cases |
| html | d3e9462 | Sebastian Gibb | 2022-06-06 | chore: rebuild site |
| html | b20484a | Sebastian Gibb | 2022-06-06 | chore: rebuild site |
| Rmd | baac1e4 | Sebastian Gibb | 2022-06-06 | fix: bootstraping elastic net |
| html | 983ec69 | Sebastian Gibb | 2022-03-17 | chore: rebuild site |
| Rmd | 057f935 | Sebastian Gibb | 2022-03-17 | feat: add elastic net bootstrap and timeROC evaluations |
library("targets")
library("ameld")
library("viridisLite")
tar_load(arcvob)
tar_load(bootrcv)
tar_load(bootrcvcc)
tar_load(bootarcv)
tar_load(bootrcv.woIC)
tar_load(amelddata)
tar_load(amelddatacc)
tar_load(ameldcfg)
tar_load(zlog_data)
tar_load(zlog_data_complete_cases)1 Tuning alpha
arcvob
Call: arcv.glmnet(x = amelddata$x, y = amelddata$y, alpha = ameldcfg$alpha, nrepcv = ameldcfg$nrepcv, nfolds = ameldcfg$nfolds, balanced = TRUE, family = "cox", standardize = ameldcfg$standardize, trace.it = FALSE)
Models: 11
Alpha: 0 0.001 0.008 0.027 0.064 0.125 0.216 0.343 0.512 0.729 1
Number of CV for Lambda: 3
Number of repeated CV for Lambda: 10
Measure: Partial Likelihood Deviance
Lambda min:
Alpha Lambda Index Measure SE Nonzero
[1,] 0.000 0.99962 72 9.016 0.3485 42
[2,] 0.001 0.99962 72 9.016 0.3483 38
[3,] 0.008 0.88152 51 9.013 0.3492 26
[4,] 0.027 0.72678 40 9.014 0.3508 20
[5,] 0.064 0.48821 35 9.027 0.3555 18
[6,] 0.125 0.36265 31 9.046 0.3585 16
[7,] 0.216 0.25279 29 9.064 0.3620 12
[8,] 0.343 0.17471 28 9.079 0.3660 12
[9,] 0.512 0.12845 27 9.093 0.3685 9
[10,] 0.729 0.09022 27 9.104 0.3725 9
[11,] 1.000 0.05993 28 9.113 0.3772 10
Lambda 1se:
Alpha Lambda Index Measure SE Nonzero
[1,] 0.000 4.8608 55 9.340 0.3201 42
[2,] 0.001 4.8608 55 9.353 0.3189 32
[3,] 0.008 3.9057 35 9.329 0.3185 23
[4,] 0.027 2.9340 25 9.361 0.3135 17
[5,] 0.064 1.9709 20 9.369 0.3123 12
[6,] 0.125 1.3340 17 9.399 0.3108 10
[7,] 0.216 0.8472 16 9.380 0.3131 8
[8,] 0.343 0.5856 15 9.403 0.3103 6
[9,] 0.512 0.4305 14 9.454 0.3054 6
[10,] 0.729 0.3024 14 9.444 0.3089 6
[11,] 1.000 0.2204 14 9.441 0.3105 6plot(arcvob)
plot(arcvob, what = "lambda.min")
plot(arcvob, what = "lambda.1se")
2 Bootstrapping
2.1 rcv.glmnet
plot(bootrcv, what = "calibration")
ps <- lapply(
zlog_data[paste0("SurvProbMeld", c("Unos", "NaUnos", "Plus7"))],
function(p) {
ctpnts <- cutpoints(p, n = ameldcfg$m)
f <- cut(p, ctpnts, include.lowest = TRUE)
list(
predicted = groupmean(p, f = f),
observed = observed_survival(
amelddata$y, f = f, times = ameldcfg$times
)
)
}
)
names(ps) <- c("MELD", "MELD-Na", "MELD-Plus7")
col <- viridisLite::viridis(6)[4:6]
for (i in seq_along(ps)) {
lines(
ps[[i]]$predicted, ps[[i]]$observed, col = col[i], type = "b", pch = 19
)
}
legend("topleft", col = col, legend = names(ps), pch = 19, bty = "n")
plot(bootrcv, what = "selected", cex = 0.5)
plot(bootrcv$fit, what = "path", xvar = "norm", nlabel = 14, cex.lab = 0.5)
plot(bootrcv$fit, what = "path", xvar = "lambda", nlabel = 14, cex.lab = 0.5)
plot(bootrcv$fit, what = "path", xvar = "dev", nlabel = 14, cex.lab = 0.5)
2.2 rcv.glmnet (complete cases only)
plot(bootrcvcc, what = "calibration")
ps <- lapply(
zlog_data_complete_cases[paste0("SurvProbMeld", c("Unos", "NaUnos", "Plus7"))],
function(p) {
ctpnts <- cutpoints(p, n = ameldcfg$m)
f <- cut(p, ctpnts, include.lowest = TRUE)
list(
predicted = groupmean(p, f = f),
observed = observed_survival(
amelddatacc$y, f = f, times = ameldcfg$times
)
)
}
)
names(ps) <- c("MELD", "MELD-Na", "MELD-Plus7")
col <- viridisLite::viridis(6)[4:6]
for (i in seq_along(ps)) {
lines(
ps[[i]]$predicted, ps[[i]]$observed, col = col[i], type = "b", pch = 19
)
}
legend("topleft", col = col, legend = names(ps), pch = 19, bty = "n")
plot(bootrcvcc, what = "selected", cex = 0.5)
plot(bootrcvcc$fit, what = "path", xvar = "norm", nlabel = 14, cex.lab = 0.5)
plot(bootrcvcc$fit, what = "path", xvar = "lambda", nlabel = 14, cex.lab = 0.5)
plot(bootrcvcc$fit, what = "path", xvar = "dev", nlabel = 14, cex.lab = 0.5)
2.3 bootrcv.woIC
Exclude IL-6 and CYSC columns from the data set.
plot(bootrcv.woIC, what = "calibration")
plot(bootrcv.woIC, what = "selected", cex = 0.5)
2.4 arcv.glmnet
a <- c(table(sapply(bootarcv$models, function(m)m$fit$alpha)))
plot(bootarcv, what = "calibration")
plot(bootarcv, what = "selected")
plot_dots(a, main = "Selected Alpha Values")
sessionInfo()R version 4.2.0 (2022-04-22)
Platform: x86_64-unknown-linux-gnu (64-bit)
Matrix products: default
BLAS/LAPACK: /gnu/store/ras6dprsw3wm3swk23jjp8ww5dwxj333-openblas-0.3.18/lib/libopenblasp-r0.3.18.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] viridisLite_0.4.0 ameld_0.0.26 survival_3.3-1 glmnet_4.1-4
[5] Matrix_1.4-1 targets_0.12.1
loaded via a namespace (and not attached):
[1] shape_1.4.6 tidyselect_1.1.2 xfun_0.31 bslib_0.3.1
[5] purrr_0.3.4 splines_4.2.0 lattice_0.20-45 vctrs_0.4.1
[9] htmltools_0.5.2 yaml_2.3.5 utf8_1.2.2 rlang_1.0.2
[13] jquerylib_0.1.4 later_1.3.0 pillar_1.7.0 glue_1.6.2
[17] withr_2.5.0 foreach_1.5.2 lifecycle_1.0.1 stringr_1.4.0
[21] workflowr_1.7.0 codetools_0.2-18 evaluate_0.15 knitr_1.39
[25] callr_3.7.0 fastmap_1.1.0 httpuv_1.6.5 ps_1.7.0
[29] fansi_1.0.3 highr_0.9 Rcpp_1.0.8.3 promises_1.2.0.1
[33] backports_1.4.1 jsonlite_1.8.0 fs_1.5.2 digest_0.6.29
[37] stringi_1.7.6 bookdown_0.26 processx_3.5.3 rprojroot_2.0.3
[41] grid_4.2.0 cli_3.3.0 tools_4.2.0 magrittr_2.0.3
[45] base64url_1.4 sass_0.4.1 tibble_3.1.7 crayon_1.5.1
[49] whisker_0.4 pkgconfig_2.0.3 ellipsis_0.3.2 data.table_1.14.2
[53] rmarkdown_2.14 iterators_1.0.14 R6_2.5.1 igraph_1.3.1
[57] git2r_0.30.1 compiler_4.2.0