200301.tirley
Automatic Nonuniform Random Variate Generation in R
Abstract
Random variate genration is an important tool in statistical
computing. Many programms for simulation or statistical computing
(e.g. R) provide a collection of random variate generators for many
standard distributions. However, as statistical modeling has become
more sophisticated there is demand for larger classes of
distributions. Adding generators for newly required distribution
seems not to be the solution to this problem. Instead so called
automatic (or blackbox) methods have been developed in the last
decade for sampling from fairly large classes of distributions with
a single piece of code. For such algorithms a data about the
distributions must be given; typically the density function (or
probability mass function), and (maybe) the (approximate) location
of the mode. In this contribution we show how such algorithms work
and suggest an interface for R as an example of a statistical library.
Mathematics Subject Classification:
65C10 (Random Number Generation)
CR Categories and Subject Descriptors:
G.3 [Probability and Statistics]: Random number generation
General Terms:
Algorithms
Key Words:
R,
nonuniform random variate generation,
universal algorithm,
automatic code generator,
transformed density rejection,
continuous distribution
Download Preprint
Postscript

PDF
Paper
Josef.Leydold@statistik.wuwien.ac.at