urgamma | R Documentation |
UNU.RAN random variate generator for the Gamma distribution
with parameters shape
and scale
.
It also allows sampling from the truncated distribution.
[Special Generator] – Sampling Function: Gamma.
urgamma(n, shape, scale=1, lb=0, ub=Inf)
n |
size of required sample. |
shape |
(strictly positive) shape parameter. |
scale |
(strictly positive) scale parameter. |
lb |
lower bound of (truncated) distribution |
ub |
upper bound of (truncated) distribution |
If scale
is omitted, it assumes the default value of 1
.
The Gamma distribution with parameters shape
= a
and scale
= s has density
f(x)= 1/(s^a Gamma(a)) x^(a-1) * exp(-x/s)
for x ≥ 0, a > 0 and s > 0.
(Here Gamma(a) is the function implemented by R's
gamma()
and defined in its help.)
The generation algorithm uses fast numerical inversion. The parameters
lb
and ub
can be used to generate variates from
the Gamma distribution truncated to the interval (lb
,ub
).
This function is a wrapper for the UNU.RAN class in R.
Compared to rgamma
, urgamma
is faster, especially for
larger sample sizes.
However, in opposition to rgamma
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
rgamma
for the R built-in generator.
## Create a sample of size 1000 x <- urgamma(n=1000,shape=2)
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