Description
Weighted Random Sampling without Replacement.
Description
A collection of implementations of classical and novel algorithms for weighted sampling without replacement.
README.md
wrswoR
The goal of wrswoR is to provide faster implementations of weighted random sampling without replacement in R.
Installation
You can install the released version of wrswoR from CRAN with:
install.packages("wrswoR")
And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("krlmlr/wrswoR")
Example
The functions in this package are a drop-in replacement to sample.int(n, size, replace = FALSE, prob = prob)
. With large n
, sample.int()
becomes too slow to be practical, unlike the functions in this package.
library(wrswoR)
set.seed(20200726)
sample_int_crank(20, 10, 1:20)
#> [1] 8 18 14 17 11 15 10 4 13 5