生成具有固定均值和sd的随机数 [英] Generate random numbers with fixed mean and sd

问题描述

使用rnorm(或runif等)在R中生成随机数时，它们很少具有准确的均值和SD作为从中采样的分布.是否有任何简单的一线或两线式为我做到这一点?作为一个初步的解决方案，我已经创建了此函数，但似乎应该是R或某些程序包的本地功能.

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)
}

说明:

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

我想要这样做的原因是，在将模拟数据应用于实际数据之前，我会对其进行调整.很好，因为有了模拟数据，我就知道了确切的属性(均值，SD等)，并且避免了p值膨胀，因为我正在做推论统计.我在问是否存在任何简单的东西，例如

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)

推荐答案

由于您要求单线运输:

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

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