Abstract：
:Selection among alternative theoretical models given an observed dataset is an important challenge in many areas of physics and astronomy. Reversible-jump Markov chain Monte Carlo (RJMCMC) is an extremely powerful technique for performing Bayesian model selection, but it suffers from a fundamental difficulty and it requires jumps between model parameter spaces, but cannot efficiently explore both parameter spaces at once. Thus, a naive jump between parameter spaces is unlikely to be accepted in the Markov chain Monte Carlo (MCMC) algorithm and convergence is correspondingly slow. Here, we demonstrate an interpolation technique that uses samples from single-model MCMCs to propose intermodel jumps from an approximation to the single-model posterior of the target parameter space. The interpolation technique, based on a kD-tree data structure, is adaptive and efficient in modest dimensionality. We show that our technique leads to improved convergence over naive jumps in an RJMCMC, and compare it to other proposals in the literature to improve the convergence of RJMCMCs. We also demonstrate the use of the same interpolation technique as a way to construct efficient 'global' proposal distributions for single-model MCMCs without prior knowledge of the structure of the posterior distribution, and discuss improvements that permit the method to be used in higher dimensional spaces efficiently.
journal_name
R Soc Open Scijournal_title
Royal Society open scienceauthors
Farr WM,Mandel I,Stevens Ddoi
10.1098/rsos.150030subject
Has Abstractpub_date
2015-06-24 00:00:00pages
150030issue
6issn
2054-5703pii
rsos150030journal_volume
2pub_type
杂志文章abstract：:Dinosaur skeletal remains are almost unknown from northern South America. One of the few exceptions comes from a small outcrop in the northernmost extension of the Andes, along the western border of Venezuela, where strata of the La Quinta Formation have yielded the ornithischian Laquintasaura venezuelae and other din...
journal_title：Royal Society open science
pub_type： 杂志文章
doi：10.1098/rsos.140184
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journal_title：Royal Society open science
pub_type： 杂志文章
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pub_type： 杂志文章
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abstract：:[This corrects the article DOI: 10.1098/rsos.180687.]. ...
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更新日期：2017-09-06 00:00:00
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更新日期：2017-03-15 00:00:00
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