Markov-normal analysis of iterative simulations before their convergence

DOI10.1016/0304-4076(95)01769-0zbMath0866.62079OpenAlexW2068379290MaRDI QIDQ1126461

Donald B. Rubin, Chuanhai Liu

Publication date: 24 July 1997

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(95)01769-0

zbMATH Keywords

EM algorithmtime seriesMarkov chain Monte Carlocovariance matrixMarkov chainmeanGibbs samplermultivariate t distributioniterative simulationsMarkov-Normal restarting procedurenearly normal

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Monte Carlo methods (65C05)

Related Items (1)

A Truncated Bivariate t Distribution

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Inference from iterative simulation using multiple sequences
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Imputation using markov chains
• Sampling-Based Approaches to Calculating Marginal Densities
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• The Calculation of Posterior Distributions by Data Augmentation
• The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence
• Monte Carlo sampling methods using Markov chains and their applications
• The Monte Carlo Method

This page was built for publication: Markov-normal analysis of iterative simulations before their convergence