Last updated: 2018-05-12
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✔ Seed:
set.seed(12345)
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✔ Session information: recorded
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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 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.4
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
loaded via a namespace (and not attached):
[1] workflowr_1.0.1 Rcpp_0.12.16 digest_0.6.15
[4] rprojroot_1.3-2 R.methodsS3_1.7.1 backports_1.1.2
[7] git2r_0.21.0 magrittr_1.5 evaluate_0.10.1
[10] stringi_1.1.6 whisker_0.3-2 R.oo_1.21.0
[13] R.utils_2.6.0 rmarkdown_1.9 tools_3.4.3
[16] stringr_1.3.0 yaml_2.1.18 compiler_3.4.3
[19] htmltools_0.3.6 knitr_1.20
This reproducible R Markdown analysis was created with workflowr 1.0.1