lfi n100 p100, compare ssvs, bb_ssl, debiased lasso
DongyueXie
2023-02-01
Last updated: 2023-02-10
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Knit directory: misc/
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Introduction
In this simulation, generate data 100 times from
\(n = 100, p = 100, \pi_0 = 0.95, \sigma^2_0 = 0.01, \sigma^2_1 = 25, \sigma^2 = 1\)
Design matrix is drawn from standard normal distribution.
res = readRDS('output/lfi/n100.rds')Coverage
The coverage is mean of (mean coverage of all parameters each time) over 100 replicates.
boxplot(res$covered)
abline(h=0.95,lty=2)
| Version | Author | Date |
|---|---|---|
| 6955549 | DongyueXie | 2023-02-10 |
CI length
get_ci_length = function(res){
n_simu = length(res)
ci_length = c()
for(i in 1:n_simu){
ci_length = rbind(ci_length,c(mean(apply(res[[i]]$fit_ssvs$beta_draws,2,function(z){quantile(z,0.975)})-apply(res[[i]]$fit_ssvs$beta_draws,2,function(z){quantile(z,0.025)})),
mean(apply(res[[i]]$fit_bb$beta,2,function(z){quantile(z,0.975)})-apply(res[[i]]$fit_bb$beta,2,function(z){quantile(z,0.025)})),
mean(res[[i]]$fit_debiased$up.lim - res[[i]]$fit_debiased$low.lim)))
}
colnames(ci_length) = c('ssvs','bb_ssl','debiased')
return(ci_length)
}
boxplot(get_ci_length(res$res))
| Version | Author | Date |
|---|---|---|
| 6955549 | DongyueXie | 2023-02-10 |
MSE
the mse of (posterior mean, and true beta)
mse = function(x,y){mean((x-y)^2)}
calc_mse = function(res){
n_simu = length(res)
mse_all = c()
for(i in 1:n_simu){
mse_all = rbind(mse_all,c(mse(res[[i]]$data$beta,colMeans(res[[i]]$fit_ssvs$beta_draws)),
mse(res[[i]]$data$beta,colMeans(res[[i]]$fit_bb$beta)),
mse(res[[i]]$data$beta,res[[i]]$fit_debiased$coef)))
}
colnames(mse_all) = c('ssvs','bb_ssl','debiased')
return(mse_all)
}
boxplot(calc_mse(res$res))
sessionInfo()R version 4.2.2 Patched (2022-11-10 r83330)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.1 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.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] workflowr_1.7.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.9 highr_0.9 compiler_4.2.2 pillar_1.8.1
[5] bslib_0.4.2 later_1.3.0 git2r_0.30.1 jquerylib_0.1.4
[9] tools_4.2.2 getPass_0.2-2 digest_0.6.31 jsonlite_1.8.4
[13] evaluate_0.19 lifecycle_1.0.3 tibble_3.1.8 pkgconfig_2.0.3
[17] rlang_1.0.6 cli_3.4.1 rstudioapi_0.14 yaml_2.3.6
[21] xfun_0.35 fastmap_1.1.0 httr_1.4.4 stringr_1.5.0
[25] knitr_1.41 fs_1.5.2 vctrs_0.5.1 sass_0.4.4
[29] rprojroot_2.0.3 glue_1.6.2 R6_2.5.1 processx_3.8.0
[33] fansi_1.0.3 rmarkdown_2.19 callr_3.7.3 magrittr_2.0.3
[37] whisker_0.4.1 ps_1.7.2 promises_1.2.0.1 htmltools_0.5.4
[41] httpuv_1.6.7 utf8_1.2.2 stringi_1.7.8 cachem_1.0.6