Recursive pathways to marginal likelihood estimation with prior-sensitivity analysis
From MaRDI portal
Publication:252729
DOI10.1214/13-STS465zbMath1331.62128arXiv1301.6450OpenAlexW2099038477WikidataQ58490576 ScholiaQ58490576MaRDI QIDQ252729
Ewan Cameron, Anthony N. Pettitt
Publication date: 4 March 2016
Published in: Statistical Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1301.6450
importance samplingpath samplingthermodynamic integrationBayes factormarginal likelihoodBayesian model selectionMetropolis-coupled Markov chain Monte Carlonested samplingnormalizing constantreverse logistic regression
Related Items
Marginal Likelihood Computation for Model Selection and Hypothesis Testing: An Extensive Review, A statistical test for nested sampling algorithms, Consistency of adaptive importance sampling and recycling schemes, Nested sampling methods, Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation, Constraining the break of spatial diffeomorphism invariance with Planck data, Bayes posterior convergence for loss functions via almost additive thermodynamic formalism
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Exact sampling and counting for fixed-margin matrices
- Estimating Bayes factors via thermodynamic integration and population MCMC
- Empirical distributions in selection bias models
- Large sample theory of empirical distributions in biased sampling models
- Conditional distributions as derivatives
- Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
- On Monte Carlo methods for estimating ratios of normalizing constants
- Bayesian model averaging: A tutorial. (with comments and a rejoinder).
- Bayesian analysis of mixture models with an unknown number of components\,--\,an alternative to reversible jump methods.
- Markov chains for exploring posterior distributions. (With discussion)
- On resolving the Savage-Dickey paradox
- Monte Carlo methods in Bayesian computation
- A path sampling identity for computing the Kullback-Leibler and J divergences
- Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
- Computing the Bayes factor from a Markov chain Monte Carlo simulation of the posterior distribution
- Properties of nested sampling
- α-Stable Limit Laws for Harmonic Mean Estimators of Marginal Likelihoods
- A Stochastic Simulation Approach to Model Selection for Stochastic Volatility Models
- Marginal Likelihood from the Gibbs Output
- Adaptive Multiple Importance Sampling
- Hyperparameter and model selection for nonparametric Bayes problems via Radon-Nikodym derivatives
- Sequential Monte Carlo Samplers
- Density Estimation With Confidence Sets Exemplified by Superclusters and Voids in the Galaxies
- Marginal Likelihood Estimation via Power Posteriors
- Invariance principles for sums of Banach space valued random elements and empirical processes
- Sequential Imputations and Bayesian Missing Data Problems
- Practical Bayesian Density Estimation Using Mixtures of Normals
- Probability Theory
- A sequential particle filter method for static models
- A Theory of Statistical Models for Monte Carlo Integration
- Weighted Average Importance Sampling and Defensive Mixture Distributions
- Bayesian Density Estimation and Inference Using Mixtures
- Bayes Factors
- Monotone Iterations for Nonlinear Equations with Application to Gauss-Seidel Methods
- Application of the Radon-Nikodym Theorem to the Theory of Sufficient Statistics
- Simulating normalizing constants: From importance sampling to bridge sampling to path sampling
- Monte Carlo strategies in scientific computing
- Nested sampling for general Bayesian computation
