Last updated: 2018-03-02
Code version: a79b566
library(mashr)
Loading required package: ashr
set.seed(2018)
data = simple_sims(500, err_sd = 0.1)
data.miss = data
missing.row = sample(1:nrow(data$Bhat), nrow(data$Bhat)/4)
missing.ind = matrix(0, nrow = nrow(data$B), ncol=ncol(data$B))
missing.ind[missing.row,] = 1
missing = which(missing.ind == 1)
data.miss$Bhat[missing] = NA
data.miss$Shat[missing] = NA
missing1 = is.na(data.miss$Bhat[,1])
# Set the missing value with large standard deviation
data.large.dev = data.miss
data.large.dev$Bhat[is.na(data.miss$Bhat)] = 0
data.large.dev$Shat[is.na(data.miss$Shat)] = 1000
Warning in REBayes::KWDual(A, rep(1, k), normalize(w), control = control): estimated mixing distribution has some negative values:
consider reducing rtol
Warning in mixIP(matrix_lik = structure(c(1, 0.204132576568413,
0.736530341806702, : Optimization step yields mixture weights that are
either too small, or negative; weights have been corrected and renormalized
after the optimization.
FIXME: 'compute_posterior_matrices' in Rcpp does not transfer EZ to EE
Warning in REBayes::KWDual(A, rep(1, k), normalize(w), control = control): estimated mixing distribution has some negative values:
consider reducing rtol
Warning in mixIP(matrix_lik = structure(c(1, 0.204132576568412,
0.736530341806701, : Optimization step yields mixture weights that are
either too small, or negative; weights have been corrected and renormalized
after the optimization.
FIXME: 'compute_posterior_matrices' in Rcpp does not transfer EZ to EE
The weights learned from the data are correct.
Warning in REBayes::KWDual(A, rep(1, k), normalize(w), control = control): estimated mixing distribution has some negative values:
consider reducing rtol
Warning in mixIP(matrix_lik = structure(c(0.240920767436896,
0.337563330121546, : Optimization step yields mixture weights that are
either too small, or negative; weights have been corrected and renormalized
after the optimization.
The estimated weights are very weird and incorrect. It ignores the null matrix.
Warning in REBayes::KWDual(A, rep(1, k), normalize(w), control = control): estimated mixing distribution has some negative values:
consider reducing rtol
Warning in mixIP(matrix_lik = structure(c(0.240920767436896,
0.33756333012155, : Optimization step yields mixture weights that are
either too small, or negative; weights have been corrected and renormalized
after the optimization.
FIXME: 'compute_posterior_matrices' in Rcpp does not transfer EZ to EE
mash.data.missing.na.1 = mash_set_data(Bhat=data.miss.na$Bhat, Shat= data.miss.na$Shat, alpha = 1)
U.c = cov_canonical(mash.data.missing.na.1)
mash.model.missing.na.1 = mash(mash.data.missing.na.1, U.c, verbose=FALSE)
Warning in REBayes::KWDual(A, rep(1, k), normalize(w), control = control): estimated mixing distribution has some negative values:
consider reducing rtol
Warning in mixIP(matrix_lik = structure(c(0.240920767436896,
0.33756333012155, : Optimization step yields mixture weights that are
either too small, or negative; weights have been corrected and renormalized
after the optimization.
FIXME: 'compute_posterior_matrices' in Rcpp does not transfer EZ to EE
barplot(get_estimated_pi(mash.model.missing.na.1), las=2, cex.names = 0.7)
The estimated weights are different.
The weired covariance structure is caused by the high dimension of R.
If we separate conditions into several groups, the covariance structure will be correct.
We show this for the EZ model R=60.
FIXME: 'compute_posterior_matrices' in Rcpp does not transfer EZ to EE
FIXME: 'compute_posterior_matrices' in Rcpp does not transfer EZ to EE
FIXME: 'compute_posterior_matrices' in Rcpp does not transfer EZ to EE
sessionInfo()
R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.3
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] mashr_0.2-6 ashr_2.2-7
loaded via a namespace (and not attached):
[1] Rcpp_0.12.15 knitr_1.20 magrittr_1.5
[4] REBayes_1.2 MASS_7.3-47 doParallel_1.0.11
[7] pscl_1.5.2 SQUAREM_2017.10-1 lattice_0.20-35
[10] foreach_1.4.4 plyr_1.8.4 stringr_1.3.0
[13] tools_3.4.3 parallel_3.4.3 grid_3.4.3
[16] rmeta_2.16 git2r_0.20.0 htmltools_0.3.6
[19] iterators_1.0.9 assertthat_0.2.0 yaml_2.1.17
[22] rprojroot_1.2 digest_0.6.13 Matrix_1.2-12
[25] codetools_0.2-15 evaluate_0.10.1 rmarkdown_1.8
[28] stringi_1.1.6 compiler_3.4.3 Rmosek_8.0.69
[31] backports_1.1.2 mvtnorm_1.0-7 truncnorm_1.0-8
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