Simulate r-scores of each training set size

Calculate r-scores (un-target) by in parallel.

Usage

nt2r(geno, nt, n_iter = 30, multi.threads = FALSE, threads = NULL)

geno: A numeric dataframe of genotype, column represent sites (genotype coding as 1, 0, -1)
nt: Numeric. Number of training set size
n_iter: Times of iteration. (default = 30)
multi.threads: Default: FALSE. If TRUE, the iterations run in parallel (OpenMP, any system with OpenMP support) on 75% of the available processors (limited by OMP_NUM_THREADS), or half of them when there are 4 or fewer.
threads: Default: NULL. The number of threads; it overrides multi.threads. The parallel iterations use their own random generators, seeded from R's generator. The values then depend on set.seed() but not on threads, and they are not those of the serial run with the same seed.

A vector of r-scores of each iteration

data(geno)
if (FALSE) nt2r(geno, 50) # \dontrun{}