# sample

0th

Percentile

##### Random Samples and Permutations

sample takes a sample of the specified size from the elements of x using either with or without replacement.

Keywords
distribution
##### Usage
sample(x, size, replace = FALSE, prob = NULL)
sample.int(n, size = n, replace = FALSE, prob = NULL)
##### Arguments
x
Either a vector of one or more elements from which to choose, or a positive integer. See ‘Details.’
n
a positive number, the number of items to choose from. See ‘Details.’
size
a non-negative integer giving the number of items to choose.
replace
Should sampling be with replacement?
prob
A vector of probability weights for obtaining the elements of the vector being sampled.
##### Details

If x has length 1, is numeric (in the sense of is.numeric) and x >= 1, sampling via sample takes place from 1:x. Note that this convenience feature may lead to undesired behaviour when x is of varying length in calls such as sample(x). See the examples.

Otherwise x can be any R object for which length and subsetting by integers make sense: S3 or S4 methods for these operations will be dispatched as appropriate.

For sample the default for size is the number of items inferred from the first argument, so that sample(x) generates a random permutation of the elements of x (or 1:x).

It is allowed to ask for size = 0 samples with n = 0 or a length-zero x, but otherwise n > 0 or positive length(x) is required.

##### References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

Ripley, B. D. (1987) Stochastic Simulation. Wiley.

RNG about random number generation.

CRAN package \href{https://CRAN.R-project.org/package=#1}{\pkg{#1}}samplingsampling for other methods of weighted sampling without replacement.

• sample
• sample.int
##### Examples
library(base) x <- 1:12 # a random permutation sample(x) # bootstrap resampling -- only if length(x) > 1 ! sample(x, replace = TRUE) # 100 Bernoulli trials sample(c(0,1), 100, replace = TRUE) ## More careful bootstrapping -- Consider this when using sample() ## programmatically (i.e., in your function or simulation)! # sample()'s surprise -- example x <- 1:10 sample(x[x > 8]) # length 2 sample(x[x > 9]) # oops -- length 10! sample(x[x > 10]) # length 0 resample <- function(x, ...) x[sample.int(length(x), ...)] resample(x[x > 8]) # length 2 resample(x[x > 9]) # length 1 resample(x[x > 10]) # length 0 ## R 3.x.y only sample.int(1e10, 12, replace = TRUE) sample.int(1e10, 12) # not that there is much chance of duplicates 
Documentation reproduced from package base, version 3.2.0, License: Part of R 3.2.0

### Community examples

Alettadieben@yahoo.nl at Mar 3, 2018 base v3.4.3

Alettadieben@yahoo.nl at Mar 3, 2018 base v3.4.3

Alettadieben@yahoo.nl at Mar 3, 2018 base v3.4.3