Generate random numbers with fixed mean and sd

Question

When generating random numbers in R using rnorm (or runif etc.), they seldom have the exact mean and SD as the distribution they are sampled from. Is there any simple one-or-two-liner that does this for me? As a preliminary solution, I've created this function but it seems like something that should be native to R or some package.

# Draw sample from normal distribution with guaranteed fixed mean and sd rnorm_fixed = function(n, mu=0, sigma=1) {   x = rnorm(n)  # from standard normal distribution   x = sigma * x / sd(x)  # scale to desired SD   x = x - mean(x) + mu  # center around desired mean   return(x) } 

To illustrate:

x = rnorm(n=20, mean=5, sd=10) mean(x)  # is e.g. 6.813... sd(x)  # is e.g. 10.222...  x = rnorm_fixed(n=20, mean=5, sd=10) mean(x)  # is 5 sd(x)  # is 10 

The reason I want this is that I adjust my analysis on simulated data before applying it to real data. This is nice because with simulated data I know the exact properties (means, SDs etc.) and I avoid p-value inflation because I'm doing inferential statistics. I am asking if there exist anything simple like e.g.

rnorm(n=20, mean=5, sd=10, fixed=TRUE) 

Answer 1

Since you asked for a one-liner:

rnorm2 <- function(n,mean,sd) { mean+sd*scale(rnorm(n)) } r <- rnorm2(100,4,1) mean(r)  ## 4 sd(r)    ## 1