vSMC: Parallel Sequential Monte Carlo in C++

Sequential Monte Carlo is a family of algorithms for sampling from a sequence of distributions. Some of these algorithms, such as particle filters, are widely used in physics and signal processing research. More recent developments have established their application in more general inference problem...

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Main Author: Yan Zhou
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2015-01-01
Series:Journal of Statistical Software
Online Access:http://www.jstatsoft.org/index.php/jss/article/view/2214
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author Yan Zhou
author_facet Yan Zhou
author_sort Yan Zhou
collection DOAJ
description Sequential Monte Carlo is a family of algorithms for sampling from a sequence of distributions. Some of these algorithms, such as particle filters, are widely used in physics and signal processing research. More recent developments have established their application in more general inference problems such as Bayesian modeling. These algorithms have attracted considerable attention in recent years not only be- cause that they have desired statistical properties, but also because they admit natural and scalable parallelization. However, they are perceived to be difficult to implement. In addition, parallel programming is often unfamiliar to many researchers though conceptually appealing. A C++ template library is presented for the purpose of implementing generic sequential Monte Carlo algorithms on parallel hardware. Two examples are presented: a simple particle filter and a classic Bayesian modeling problem.
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spelling doaj.art-be38dabfb9d943f29dd0e4e48cd0c38c2022-12-22T02:47:36ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602015-01-0162114910.18637/jss.v062.i09818vSMC: Parallel Sequential Monte Carlo in C++Yan ZhouSequential Monte Carlo is a family of algorithms for sampling from a sequence of distributions. Some of these algorithms, such as particle filters, are widely used in physics and signal processing research. More recent developments have established their application in more general inference problems such as Bayesian modeling. These algorithms have attracted considerable attention in recent years not only be- cause that they have desired statistical properties, but also because they admit natural and scalable parallelization. However, they are perceived to be difficult to implement. In addition, parallel programming is often unfamiliar to many researchers though conceptually appealing. A C++ template library is presented for the purpose of implementing generic sequential Monte Carlo algorithms on parallel hardware. Two examples are presented: a simple particle filter and a classic Bayesian modeling problem.http://www.jstatsoft.org/index.php/jss/article/view/2214
spellingShingle Yan Zhou
vSMC: Parallel Sequential Monte Carlo in C++
Journal of Statistical Software
title vSMC: Parallel Sequential Monte Carlo in C++
title_full vSMC: Parallel Sequential Monte Carlo in C++
title_fullStr vSMC: Parallel Sequential Monte Carlo in C++
title_full_unstemmed vSMC: Parallel Sequential Monte Carlo in C++
title_short vSMC: Parallel Sequential Monte Carlo in C++
title_sort vsmc parallel sequential monte carlo in c
url http://www.jstatsoft.org/index.php/jss/article/view/2214
work_keys_str_mv AT yanzhou vsmcparallelsequentialmontecarloinc