AR: Another Look at the Acceptance-Rejection Method

In mathematics, 'rejection sampling' is a basic technique used to generate observations from a distribution. It is also commonly called 'the Acceptance-Rejection method' or 'Accept-Reject algorithm' and is a type of Monte Carlo method. 'Acceptance-Rejection method' is based on the observation that to sample a random variable one can perform a uniformly random sampling of the 2D cartesian graph, and keep the samples in the region under the graph of its density function. Package 'AR' is able to generate/simulate random data from a probability density function by Acceptance-Rejection method. Moreover, this package is a useful teaching resource for graphical presentation of Acceptance-Rejection method. From the practical point of view, the user needs to calculate a constant in Acceptance-Rejection method, which package 'AR' is able to compute this constant by optimization tools. Several numerical examples are provided to illustrate the graphical presentation for the Acceptance-Rejection Method.

Version: 1.0
Imports: DISTRIB
Published: 2017-05-18
Author: Abbas Parchami (Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran)
Maintainer: Abbas Parchami <parchami at uk.ac.ir>
License: LGPL (≥ 3)
NeedsCompilation: no
CRAN checks: AR results

Downloads:

Reference manual: AR.pdf
Package source: AR_1.0.tar.gz
Windows binaries: r-devel: AR_1.0.zip, r-release: AR_1.0.zip, r-oldrel: AR_1.0.zip
OS X El Capitan binaries: r-release: AR_1.0.tgz
OS X Mavericks binaries: r-oldrel: AR_1.0.tgz

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