Last updated: 2017-12-21

Code version: 6e42447

Introduction

We are doing large-scale simulation using CASH and other methods, with emphasis on the accuracy of FDR calibration.

All data sets on average, including both over-dispersion, under-dispersion, and else

source("../code/gdash_lik.R")
z.mat = readRDS("../output/z_null_liver_777.rds")
se.mat = readRDS("../output/sebetahat_null_liver_777.rds")

Session information

sessionInfo()
R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.2

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/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] ashr_2.2-2        Rmosek_8.0.69     PolynomF_1.0-1    CVXR_0.94-4      
[5] REBayes_1.2       Matrix_1.2-12     SQUAREM_2017.10-1 EQL_1.0-0        
[9] ttutils_1.0-1    

loaded via a namespace (and not attached):
 [1] gmp_0.5-13.1      Rcpp_0.12.14      compiler_3.4.3   
 [4] git2r_0.20.0      R.methodsS3_1.7.1 R.utils_2.6.0    
 [7] iterators_1.0.9   tools_3.4.3       digest_0.6.13    
[10] bit_1.1-12        evaluate_0.10.1   lattice_0.20-35  
[13] foreach_1.4.4     yaml_2.1.16       parallel_3.4.3   
[16] Rmpfr_0.6-1       ECOSolveR_0.3-2   stringr_1.2.0    
[19] knitr_1.17        rprojroot_1.3-1   bit64_0.9-7      
[22] grid_3.4.3        R6_2.2.2          rmarkdown_1.8    
[25] magrittr_1.5      MASS_7.3-47       backports_1.1.2  
[28] codetools_0.2-15  htmltools_0.3.6   scs_1.1-1        
[31] stringi_1.1.6     doParallel_1.0.11 pscl_1.5.2       
[34] truncnorm_1.0-7   R.oo_1.21.0

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