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Authors: Adam M. Johansen
Title: [download]
(16037)
SMCTC: Sequential Monte Carlo in C++
Reference: Vol. 30, Issue 6, Apr 2009
Submitted 2008-08-29, Accepted 2009-03-24
Type: Article
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.

Paper: [download]
(16037)
SMCTC: Sequential Monte Carlo in C++
(application/pdf, 626.2 KB)
Supplements: [download]
(3349)
smctc-1.0.zip: C++ source code for SMTC library including all examples
(application/zip, 97.3 KB)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.
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