rbeta {rBeta2009} | R Documentation |
The Beta Random Number Generating Function
Description
Random generation for the beta distribution with parameters shape1
and
shape2
.
Usage
rbeta(n, shape1, shape2)
Arguments
n |
Number of beta random numbers to generate. If |
shape1 , shape2 |
Positive shape parameters. |
Details
The beta distribution with parameters shape1
and
shape2
has density
for and
.
The mean is and the variance is
.
rbeta
basically utilizes the following guideline primarily proposed by Hung
et al. (2009) for generating beta random numbers.
When
shape1
shape2
, the B00 algorithm (Sakasegawa, 1983) is used;
When
shape1
shape2
orshape1
shape2
, the B01 algorithm (Sakasegawa, 1983) is used;When
shape1
shape1
, the B4PE algorithm (Schmeiser and Babu, 1980) is used if one papameter is close to 1 and the other is large (say
); otherwise, the BPRS algorithm (Zechner and Stadlober, 1993) is used.
Value
rbeta
generates beta random numbers.
Author(s)
Ching-Wei Cheng <aks43725@gmail.com>,
Ying-Chao Hung <hungy@nccu.edu.tw>,
Narayanaswamy Balakrishnan <bala@univmail.cis.mcmaster.ca>
Source
rbeta
uses a C translation of
Y. C. Hung and N. Balakrishnan and Y. T. Lin (2009), Evaluation of beta generation algorithms, Communications in Statistics - Simulation and Computation, 38:750–770.
References
Y. C. Hung and N. Balakrishnan and Y. T. Lin (2009), Evaluation of beta generation algorithms, Communications in Statistics - Simulation and Computation, 38, 750–770.
H. Sakasegawa (1983), Stratified rejection and squeeze method for generating beta random numbers, Annals of the Institute Statistical Mathematics, 35, 291–302.
B.W. Schmeiser and A.J.G. Babu (1980), Beta variate generation via exponential majorizing functions, Operations Research, 28, 917–926.
H. Zechner and E. Stadlober (1993), Generating beta variates via patchwork rejection, Computing, 50, 1–18.
See Also
rbeta
in package stats.
Examples
library(rBeta2009)
rbeta(10, 0.7, 1.5)