urnorm | 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.
[Special Generator] – 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.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)
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