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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.
Getting started
Browse package contents
Package details |
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| Author | Abbas Parchami (Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran) |
| Maintainer | Abbas Parchami <parchami@uk.ac.ir> |
| License | LGPL (>= 3) |
| Version | 1.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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