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author: Piotr Sulewski, Pomeranian University in Slupsk, Poland
Random generation for the normal distribution is presented. To read more about the package please see (and cite :)) papers:
Sulewski P., Drapella A. (2026). An Efficient and Precise Quantile Mapping for Normal Pseudo-Random Number Generation. Journal of Statistical Software, Under review.
You can install the released version of NormGen from CRAN with:
install.packages("NormGen")You can install the development version of NormGen from GitHub with:
library("remotes")
install_github("PiotrSule/NormGen")Standard, high-performance pseudo-normal random number generation based on an optimized quantile mapping algorithm.
library(NormGen)
# Generate 10 random numbers from N(2, 4)
Rnorm(10, m = 2, s = 2)
#> [1] 2.7330164 0.8988458 -0.1690484 2.3681542 3.5832490 1.9752853 2.1125923 1.8527157
#> [9] 2.6327170 2.7305332
# Generate 10 standard normal numbers N(0, 1)
Rnorm(10)
#> [1] -0.481834073 0.070919666 0.100871525 0.228601729 -0.622437488 -0.006578594
#> [7] -0.125655220 0.325686814 -0.352871726 -0.332205368High-performance, multithreaded pseudo-normal random number generator
powered by RcppParallel and Intel TBB. It
splits the simulation payload across available CPU cores, making it
extremely efficient for massive sample sizes (n ≥ 10⁵). It includes an
explicit seed parameter to guarantee computational
reproducibility.
# Generate parallel numbers with explicit reproducibility parameter
parallel_samples <- PRnorm(10, mean = 2, sd = 2, seed = 2026)
parallel_samples
#> [1] 4.45466992 -0.24577313 -1.50696356 3.88024531 2.16097564 5.41857159
#> [7] 1.80885156 4.86104178 1.35706814 -0.03064803
# Verify reproducibility
verify_samples <- PRnorm(10, mean = 2, sd = 2, seed = 2026)
identical(parallel_samples, verify_samples)
#> [1] TRUE
# Standard parallel generation using default N(0, 1) parameters
PRnorm(10, seed = 2026)
#> [1] 1.22733496 -1.12288656 -1.75348178 0.94012265 0.08048782 1.70928580
#> [7] -0.09557422 1.43052089 -0.32146593 -1.01532402These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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