Generate matrix with iid normal random variables using R

问题

Is there a way to generate a data set with normally distributed random values in R without using a loop? Each entry would represent an independent random variable with a normal distribution.

回答1:

To create an N by M matrix of iid normal random variables type this:

matrix( rnorm(N*M,mean=0,sd=1), N, M) 

tweak the mean and standard deviation as desired.

回答2:

let mu be a vector of means and sigma a vector of standard devs

mu<-1:10
sigma<-10:1
sample.size<-100
norm.mat<-mapply(function(x,y){rnorm(x,y,n=sample.size)},x=mu,y=sigma)

would produce a matrix with columns holding the relevant samples

回答3:

You can use:

replicate(NumbOfColumns,rnorm(NumbOfLines))

You can replace rnorm with other distribution function, for example runif, to generate matrices with other distributions.

回答4:

Notice: each entry is independent. So you cannot avoid using for loops, because you have to call rnorm once for each independent variable. If you just call rnorm(n*m) that's the n*m samples from the same random variable!

来源：https://stackoverflow.com/questions/11640415/generate-matrix-with-iid-normal-random-variables-using-r