A new Monte Carlo method for estimating marginal likelihoods
type: Item
instance of: scholarly article
title: A new Monte Carlo method for estimating marginal likelihoods
zbMATH Open document ID: 1407.62412
DOI: 10.1214/17-BA1049
author: Yubo Wang
author: Ming-Hui Chen
author: Lynn Kuo
author: Paul O. Lewis
published in: Bayesian Analysis
publication date: 2018-12-06T00:00:00Z
full work available at URL: https://projecteuclid.org/euclid.ba/1488250818
Mathematics Subject Classification ID: 62P10
Mathematics Subject Classification ID: 62F15
zbMATH DE Number: 6989950
zbMATH Keywords: Bayesian model selection
zbMATH Keywords: cure rate model
zbMATH Keywords: harmonic mean estimator
zbMATH Keywords: inflated density ratio estimator
zbMATH Keywords: ordinal probit regression
zbMATH Keywords: power prior
describes a project that uses: R
MaRDI profile type: Publication
Wikidata QID: Q55022174
cites work: Bayesian Analysis of Binary and Polychotomous Response Data
cites work: Computing marginal likelihoods from a single MCMC output
cites work: A New Bayesian Model for Survival Data with a Surviving Fraction
cites work: Discussion of ``Equi-energy sampler'' by Kou, Zhou and Wong
cites work: Partition-weighted Monte Carlo estimation
cites work: Marginal Likelihood from the Gibbs Output
cites work: Marginal Likelihood From the Metropolis–Hastings Output
cites work: Marginal Likelihood Estimation via Power Posteriors
cites work: Q4298922
cites work: Bayesian Inference in Econometric Models Using Monte Carlo Integration
cites work: Reparameterizing the generalized linear model to accelerate gibbs sampler convergence
cites work: Q4280410
cites work: A geometric approach to transdimensional markov chain monte carlo
description: scientific article; zbMATH DE number 6989950