| urnorm {Runuran} | R Documentation |
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.
[Distribution] – Sampling Function: Normal (Gaussian).
urnorm(n, mean = 0, sd = 1, lb = -Inf, ub = Inf)
n |
size of required sample. |
mean |
mean of distribution. |
sd |
standard deviation. |
lb |
lower bound of (truncated) distribution. |
ub |
upper bound of (truncated) distribution. |
If mean or sd are not specified they assume the default
values of 0 and 1, respectively.
The normal distribution has density
f(x) = 1/(sqrt(2 pi) sigma) e^-((x - mu)^2/(2 sigma^2))
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).
This function is a wrapper for the UNU.RAN class in R.
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.
Josef Leydold and Wolfgang H"ormann unuran@statmath.wu-wien.ac.at.
W. H"ormann, J. Leydold, and G. Derflinger (2004): Automatic Nonuniform Random Variate Generation. Springer-Verlag, Berlin Heidelberg
runif and .Random.seed about random number
generation, unuran for the UNU.RAN class, and
rnorm for the R built-in normal random variate
generator.
## Create a sample of size 1000 x <- urnorm(n=1000)