Monte Carlo Methods, Univariate and Multivariate

Cathal D. Walsh

doi:10.1002/9780470061572.eqr450

Monte Carlo Methods, Univariate and Multivariate

Cathal D. Walsh

Trinity College Dublin

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

With the prevalence of high-powered computing, Monte Carlo methods are increasingly used in a wide range of disciplines. In this article we review some of the principles behind these methods, note the relationship with other techniques used in systems reliability, and demonstrate some methods in practice. In particular, the accept–reject algorithm, the importance sampler, the method of compositions and the specific case of Box–Muller transformation are highlighted here.

Original language	English
Title of host publication	Encyclopedia of Statistics in Quality and Reliability
Publisher	wiley
Pages	1-6
Number of pages	6
ISBN (Electronic)	9780470061572
ISBN (Print)	9780470018613
DOIs	https://doi.org/10.1002/9780470061572.eqr450
Publication status	Published - 1 Jan 2008
Externally published	Yes

Keywords

Box–Muller
composition
correlation
ensemble methods
importance sampling
Monte Carlo
rejection

Access to Document

10.1002/9780470061572.eqr450

Cite this

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KW - Box–Muller

KW - composition

KW - correlation

KW - ensemble methods

KW - importance sampling

KW - Monte Carlo

KW - rejection

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PB - wiley

ER -

Monte Carlo Methods, Univariate and Multivariate

Abstract

Keywords

Access to Document

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