cashr
Last updated: 2018-10-07
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Document the correlated \(N(0, 1)\) figure in the cashr
paper.
source("../code/gdash_lik.R")
Loading required package: EQL
Loading required package: ttutils
Loading required package: SQUAREM
Loading required package: REBayes
Loading required package: Matrix
Loading required package: CVXR
Attaching package: 'CVXR'
The following object is masked from 'package:stats':
power
Loading required package: PolynomF
Warning: package 'PolynomF' was built under R version 3.4.4
Loading required package: Rmosek
Loading required package: ashr
Attaching package: 'ashr'
The following object is masked from 'package:CVXR':
get_np
source("../code/gdfit.R")
z.mat <- readRDS("../output/z_null_liver_777.rds")
sel = c(32, 327, 355, 483)
z.sel <- z.mat[sel, ]
gd.ord <- 10
x.plot = seq(- max(abs(z.sel)) - 2, max(abs(z.sel)) + 2, length = 1000)
hermite = Hermite(gd.ord)
gd0.std = dnorm(x.plot)
matrix_lik_plot = cbind(gd0.std)
for (j in 1 : gd.ord) {
gd.std = (-1)^j * hermite[[j]](x.plot) * gd0.std / sqrt(factorial(j))
matrix_lik_plot = cbind(matrix_lik_plot, gd.std)
}
z = z.sel[4, ]
w <- gdfit(z, gd.ord, w.lambda = 10, w.rho = 0.5)$w
y.plot = matrix_lik_plot %*% w
z.hist = hist(z, breaks = 100, plot = FALSE)
y.max = max(z.hist$density, y.plot, dnorm(0))
setEPS()
postscript("../output/paper/cor_z_hist.eps", width = 8, height = 6)
#pdf("../output/paper/cor_z_hist.pdf", width = 8, height = 6)
par(mfrow = c(2, 2)) # 2-by-2 grid of plots
par(oma = c(0.5, 2.5, 0, 0)) # make room (i.e. the 4's) for the overall x and y axis titles
par(mar = c(2, 2, 3.5, 1)) # make the plots be closer together
# now plot the graphs with the appropriate axes removed (via xaxt and yaxt),
# remove axis labels (so that they are not redundant with overall labels,
# and set some other nice choices for graphics parameters
for (i in 1 : 4) {
z = z.sel[i, ]
w <- gdfit(z, gd.ord)$w
y.plot = matrix_lik_plot %*% w
z.hist = hist(z, breaks = 100, plot = FALSE)
hist(z, breaks = 100, prob = TRUE, ylim = c(0, y.max), main = NULL, xlab = "", xlim = range(c(abs(z.sel), -abs(z.sel))))
lines(x.plot, dnorm(x.plot), col = "blue", lwd = 2)
lines(x.plot, y.plot, col = "red", lwd = 2)
legend("topleft", bty = "n", paste0('(', letters[i], ')'), cex = 1.25)
}
# print the overall labels
mtext('Density', side = 2, outer = TRUE, line = 1)
mtext("Histograms of Correlated N(0,1) Variates", line = -2, outer = TRUE)
legend("topleft", inset = c(-0.65, -0.25), legend = c("N(0, 1)", "Gaussian Derivatives"), lty = 1, lwd = 2, xpd = NA, col = c("blue", "red"), ncol = 2)
dev.off()
quartz_off_screen
2
sessionInfo()
R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6
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_2.2-3 Rmosek_8.0.69 PolynomF_1.0-2 CVXR_0.99
[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_0.5-13.2 Rcpp_0.12.18 compiler_3.4.3
[4] git2r_0.21.0 workflowr_1.1.1 R.methodsS3_1.7.1
[7] R.utils_2.7.0 iterators_1.0.9 tools_3.4.3
[10] digest_0.6.15 bit_1.1-12 evaluate_0.10.1
[13] lattice_0.20-35 foreach_1.4.4 yaml_2.1.18
[16] parallel_3.4.3 Rmpfr_0.7-1 ECOSolveR_0.4
[19] stringr_1.3.0 knitr_1.20 rprojroot_1.3-2
[22] bit64_0.9-7 grid_3.4.3 R6_2.2.2
[25] rmarkdown_1.9 magrittr_1.5 whisker_0.3-2
[28] MASS_7.3-50 backports_1.1.2 codetools_0.2-15
[31] htmltools_0.3.6 scs_1.1-1 stringi_1.1.6
[34] pscl_1.5.2 doParallel_1.0.11 truncnorm_1.0-7
[37] R.oo_1.22.0
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