urnorm function

UNU.RAN Normal random variate generator

UNU.RAN random variate generator for the Normal distribution with mean equal to mean and standard deviation to sd. It also allows sampling from the truncated distribution.

[Special Generator] -- Sampling Function: Normal (Gaussian).

urnorm(n, mean = 0, sd = 1, lb = -Inf, ub = Inf)

Arguments

• n: size of required sample.
• mean: mean of distribution.
• sd: standard deviation.
• lb: lower bound of (truncated) distribution.
• ub: upper bound of (truncated) distribution.

Details

If mean or sd are not specified they assume the default values of 0 and 1, respectively.

The normal distribution has density

where $mu$ is the mean of the distribution and $sigma$ the standard deviation.

The generation algorithm uses fast numerical inversion. The parameters lb and ub can be used to generate variates from the Normal distribution truncated to the interval (lb,ub).

See Also

runif and .Random.seed about random number generation, unuran for the UNU.RAN class, and rnorm for the built-in normal random variate generator.

References

W. H"ormann, J. Leydold, and G. Derflinger (2004): Automatic Nonuniform Random Variate Generation. Springer-Verlag, Berlin Heidelberg

Author(s)

Josef Leydold and Wolfgang H"ormann unuran@statmath.wu.ac.at .

Note

This function is a wrapper for the UNU.RAN class in . Compared to rnorm, urnorm is faster, especially for larger sample sizes. However, in opposition to rnorm vector arguments are ignored, i.e. only the first entry is used.

Examples

## Create a sample of size 1000
x <- urnorm(n=1000)