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SMCTC : sequential Monte Carlo in C++

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Johansen, Adam M.. (2009) SMCTC : sequential Monte Carlo in C++. Journal of Statistical Software, Vol.30 (No.6). pp. 1-41. ISSN 1548-7660

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Abstract

Sequential Monte Carlo methods are a very general class of Monte Carlo methods for sampling from sequences of distributions. Simple examples of these algorithms are used very widely in the tracking and signal processing literature. Recent developments illustrate that these techniques have much more general applicability, and can be applied very effectively to statistical inference problems. Unfortunately, these methods are often perceived as being computationally expensive and difficult to implement. This article seeks to address both of these problems. A C++ template class library for the efficient and convenient implementation of very general Sequential Monte Carlo algorithms is presented. Two example applications are provided: a simple particle filter for illustrative purposes and a state-of-the-art algorithm for rare event estimation.

Item Type:	Journal Article
Subjects:	H Social Sciences > HA Statistics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Monte Carlo method -- Computer programs, Statistics -- Computer programs, C++ (Computer program language)
Journal or Publication Title:	Journal of Statistical Software
Publisher:	University of California, Los Angeles
ISSN:	1548-7660
Date:	April 2009
Volume:	Vol.30
Number:	No.6
Page Range:	pp. 1-41
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
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URI:	http://wrap.warwick.ac.uk/id/eprint/2194