Last updated: 2019-10-23

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File Version Author Date Message
Rmd 7fbc1f9 zihao12 2019-10-23 update Compare_ebvaepm_ebpm.Rmd
html 66940d1 zihao12 2019-10-23 Build site.
html 234f9af zihao12 2019-10-23 Build site.
Rmd b33470b zihao12 2019-10-23 update compare vae with ebpm
html 4be9b78 zihao12 2019-10-23 Build site.
Rmd cef9f2e zihao12 2019-10-23 update compare vae with ebpm
html 6954317 zihao12 2019-10-23 Build site.
Rmd 7f57658 zihao12 2019-10-23 compare vae with ebpm

Here I show and compare the results from ebvae_pm and ebpmf. ebvae_pm was implemented and experimented here: https://zihao12.github.io/ebpmf_demo/ebvae-poisson-normal.html .

Now ebvae_pm does much worse even than the mle. It seems to be shrinking too much.

devtools::load_all("../ebpm")
Loading ebpm
library(ggplot2)
library(reticulate)

show VAE results

vae_out = py_load_object("data/poisson-normal.pkl", pickle = "pickle")
vae_out = data.frame(vae_out)

## This is what data looks like
ggplot(vae_out)+
  geom_histogram(aes(x = x), bins = 100)

Version Author Date
4be9b78 zihao12 2019-10-23
6954317 zihao12 2019-10-23 
ggplot(vae_out)+
  geom_point(aes(x = x, y = posterior_vae))

Version Author Date
4be9b78 zihao12 2019-10-23

Compare with EBPM

library(ebpm)
fit_ebpm = ebpm_exponential_mixture(as.vector(vae_out$x), s = 1, m = 2^0.25)
vae_out[["posterior_ebpm"]] = fit_ebpm$posterior$mean
ggplot(vae_out)+
  geom_point(aes(x = x, y = posterior_ebpm))

Version Author Date
4be9b78 zihao12 2019-10-23
6954317 zihao12 2019-10-23 
## biggest weight
max(fit_ebpm$fitted_g$pi)
[1] 1
## the mean  of the exponential component corresponding to the biggest weight
fit_ebpm$fitted_g$scale[which.max(fit_ebpm$fitted_g$pi)]
[1] 10.76347

Compare RMSE

## rmse(fit_vae, lam)
sqrt(mean((vae_out$posterior_vae - vae_out$lam)^2))
[1] 5.788469
## rmse(fit_ebpm, lam)
sqrt(mean((fit_ebpm$posterior$mean - vae_out$lam)^2))
[1] 2.962624
## rmse(mle, lam)
sqrt(mean((vae_out$x- vae_out$lam)^2))
[1] 3.197445

sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
[1] reticulate_1.12 ggplot2_3.2.1   ebpm_0.0.0.9001 testthat_2.2.1 

loaded via a namespace (and not attached):
 [1] gtools_3.8.1        tidyselect_0.2.5    xfun_0.8           
 [4] remotes_2.1.0       purrr_0.3.2         lattice_0.20-38    
 [7] colorspace_1.4-1    usethis_1.5.1       htmltools_0.3.6    
[10] yaml_2.2.0          rlang_0.4.0         pkgbuild_1.0.3     
[13] mixsqp_0.1-121      pillar_1.4.2        glue_1.3.1         
[16] withr_2.1.2         sessioninfo_1.1.1   stringr_1.4.0      
[19] munsell_0.5.0       gtable_0.3.0        workflowr_1.4.0    
[22] devtools_2.2.1.9000 memoise_1.1.0       evaluate_0.14      
[25] labeling_0.3        knitr_1.25          callr_3.2.0        
[28] ps_1.3.0            Rcpp_1.0.2          backports_1.1.5    
[31] scales_1.0.0        desc_1.2.0          pkgload_1.0.2      
[34] jsonlite_1.6        fs_1.3.1            digest_0.6.22      
[37] stringi_1.4.3       processx_3.3.1      dplyr_0.8.1        
[40] rprojroot_1.3-2     grid_3.5.1          cli_1.1.0          
[43] tools_3.5.1         magrittr_1.5        lazyeval_0.2.2     
[46] tibble_2.1.3        crayon_1.3.4        whisker_0.3-2      
[49] pkgconfig_2.0.3     ellipsis_0.3.0      Matrix_1.2-17      
[52] prettyunits_1.0.2   assertthat_0.2.1    rmarkdown_1.13     
[55] rstudioapi_0.10     R6_2.4.0            git2r_0.25.2       
[58] compiler_3.5.1