The Generalized Multiset Sampler: Theory and Its Application

The Generalized Multiset Sampler: Theory and Its Application

Bibliographic Details
Main Author: Kim, Hang Joon
Language:English
Published: The Ohio State University / OhioLINK 2012
Subjects:
Statistics
Advanced MCMC
Metropolis
Importance sampling
Mixture model
Local trap
Gene expression study
Multimodality
Bimodality
Simultaneous equation
Outlier detection
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=osu1338332071
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-osu13383320712021-08-03T06:05:34Z The Generalized Multiset Sampler: Theory and Its Application Kim, Hang Joon Statistics Advanced MCMC Metropolis Importance sampling Mixture model Local trap Gene expression study Multimodality Bimodality Simultaneous equation Outlier detection The multiset sampler (MSS) proposed by Leman et al. (2009) is a new MCMC algorithm, especially useful to draw samples from a multimodal distribution, and easy to implement. We generalize the algorithm by re-defining the MSS with an explicit description of the link between a target distribution and a limiting distribution. The generalized formulation makes the idea of the multiset (or K-tuple) applicable not only to Metropolis-Hastings algorithms, but also to other sampling methods, both static and adaptive. The basic properties of implied distributions and methods are provided. Drawing on results from importance sampling, we also create effective estimators for both the basic multiset sampler and the generalization we propose. Simulation and practical examples confirm that the generalized multiset sampler (GMSS) provides a general and easy approach to dealing with multimodality and improving a chain’s mixing. 2012-06-25 English text The Ohio State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=osu1338332071 http://rave.ohiolink.edu/etdc/view?acc_num=osu1338332071 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Statistics
Advanced MCMC
Metropolis
Importance sampling
Mixture model
Local trap
Gene expression study
Multimodality
Bimodality
Simultaneous equation
Outlier detection
spellingShingle Statistics
Advanced MCMC
Metropolis
Importance sampling
Mixture model
Local trap
Gene expression study
Multimodality
Bimodality
Simultaneous equation
Outlier detection
Kim, Hang Joon
The Generalized Multiset Sampler: Theory and Its Application
author Kim, Hang Joon
author_facet Kim, Hang Joon
author_sort Kim, Hang Joon
title The Generalized Multiset Sampler: Theory and Its Application
title_short The Generalized Multiset Sampler: Theory and Its Application
title_full The Generalized Multiset Sampler: Theory and Its Application
title_fullStr The Generalized Multiset Sampler: Theory and Its Application
title_full_unstemmed The Generalized Multiset Sampler: Theory and Its Application
title_sort generalized multiset sampler: theory and its application
publisher The Ohio State University / OhioLINK
publishDate 2012
url http://rave.ohiolink.edu/etdc/view?acc_num=osu1338332071
work_keys_str_mv AT kimhangjoon thegeneralizedmultisetsamplertheoryanditsapplication
AT kimhangjoon generalizedmultisetsamplertheoryanditsapplication
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