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I am simulating data using rnorm, but I need to set an upper and lower limit, does anyone know how to do this?
code:
rnorm(n = 10, mean = 39.74, sd = 25.09)
Upper limit needs to be 340, and the lower limit 0
I am asking this question because I am rewriting an SAS-code into an R-code. I have never used SAS. I am trying to rewrite the following piece of code:
sim_sample(simtot=100000,seed=10004,lbound=0,ubound=340,round_y=0.01,round_m=0.01,round_sd=0.01,n=15,m=39.74,sd=25.11,mk=4)
870
rnorm is the R function that simulates random variates having a specified normal distribution. As with pnorm , qnorm , and dnorm , optional arguments specify the mean and standard deviation of the distribution.
If we want to generate standard normal random numbers then rnorm function of R can be used but need to pass the mean = 0 and standard deviation = 1 inside this function.
If you want to generate a vector of normally distributed random numbers, rnorm is the function you should use. The first argument n is the number of numbers you want to generate, followed by the standard mean and sd arguments.
The rnorm() function in R generates a random number using a normal(bell curve) distribution. Thus, the rnorm() function simulates random variates having a specified normal distribution.
The rtruncnorm() function will return the results you need.
library(truncnorm)
rtruncnorm(n=10, a=0, b=340, mean=39.4, sd=25.09)
You can make your own truncated normal sampler that doesn't require you to throw out observations quite simply
rtnorm <- function(n, mean, sd, a = -Inf, b = Inf){
qnorm(runif(n, pnorm(a, mean, sd), pnorm(b, mean, sd)), mean, sd)
}
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