# check empirical normal score transform
library(CopulaModel)
for(n in seq(100,1000,100)) { cat(n," ",nscoreOpta(n),"\n") }
#100 -0.5766102
#200 -0.5673076
#300 -0.5627994
#400 -0.559935
#500 -0.5578796
#600 -0.5562977
#700 -0.5550235
#800 -0.5539637
#900 -0.5530609
#1000 -0.5522775
# check nscore for vectors and matrices
x=1:20
nscoreOpta(length(x))
print(nscore(x))
# [1] -1.95996398 -1.43953147 -1.15034938 -0.93458929 -0.75541503 -0.59776013
# [7] -0.45376219 -0.31863936 -0.18911843 -0.06270678 0.06270678 0.18911843
#[13] 0.31863936 0.45376219 0.59776013 0.75541503 0.93458929 1.15034938
#[19] 1.43953147 1.95996398
print(nscore(x,iopt=T))
# [1] -2.06080784 -1.47413428 -1.17107282 -0.94885656 -0.76576249 -0.60535717
# [7] -0.45923451 -0.32234699 -0.19127021 -0.06341258 0.06341258 0.19127021
#[13] 0.32234699 0.45923451 0.60535717 0.76576249 0.94885656 1.17107282
#[19] 1.47413428 2.06080784
print(nscore(cbind(x,rev(x))))
print(nscore(cbind(x,rev(x)),iopt=T))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.