Implementation by Rmosek: Simulated Non-Null

Introduction

We are exploring the GD-ASH method to fit \(g\) and the empirical null together.

z <- read.table("../output/z_null_liver_777.txt")
n = ncol(z)

sel <- c(32, 327, 355, 483, 778)
ord <- c(4, 9, 9, 4, 4)
sel.num = length(sel)

beta <- c(
  rep(0, 6000),
  rnorm(3000, 0, 2),
  rnorm(1000, 0, 4)
)
beta <- sample(beta)
sebetahat <- rep(1, 1e4)
betahat.mat <- matrix(0, nrow = sel.num, ncol = n)
for (i in 1 : sel.num) {
  betahat.mat[i, ] = beta + sebetahat * as.numeric(z[sel[i], ])
}

source("../code/gdash.R")

Session information

sessionInfo()

R version 3.3.3 (2017-03-06)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra 10.12.4

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     

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.10      lattice_0.20-34   codetools_0.2-15 
 [4] digest_0.6.11     foreach_1.4.3     rprojroot_1.2    
 [7] truncnorm_1.0-7   MASS_7.3-45       grid_3.3.3       
[10] backports_1.0.5   git2r_0.18.0      magrittr_1.5     
[13] evaluate_0.10     stringi_1.1.2     pscl_1.4.9       
[16] doParallel_1.0.10 rmarkdown_1.3     iterators_1.0.8  
[19] tools_3.3.3       stringr_1.2.0     parallel_3.3.3   
[22] yaml_2.1.14       ashr_2.1-10       SQUAREM_2016.10-1
[25] htmltools_0.3.5   knitr_1.15.1