Last updated: 2017-06-04
Code version: fad7789
This time the correlated \(z\) scores are simulated similar to the previous low rank example but with different numbers of \(k\).
n = 1e4
L = 100
set.seed(777)
k = 1
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
set.seed(777)
k = 2
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
set.seed(777)
k = 3
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
set.seed(777)
k = 4
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
set.seed(777)
k = 5
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
set.seed(777)
k = 6
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
set.seed(777)
k = 7
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
set.seed(777)
k = 8
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
set.seed(777)
k = 9
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
set.seed(777)
k = 10
for (j in 1 : 2) {
z = z.sim(n, k)
fit.gd(L, z)
}
sessionInfo()
R version 3.3.3 (2017-03-06)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra 10.12.5
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] backports_1.0.5 magrittr_1.5 rprojroot_1.2 tools_3.3.3
[5] htmltools_0.3.6 yaml_2.1.14 Rcpp_0.12.11 stringi_1.1.2
[9] rmarkdown_1.5 knitr_1.16 git2r_0.18.0 stringr_1.2.0
[13] digest_0.6.12 evaluate_0.10
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