Equation-solving estimator based on the general n-step MHDR algorithm

DOI10.1080/00949655.2019.1632858OpenAlexW2949838112MaRDI QIDQ5107487

Hatem Baffoun, Mekki Hajlaoui

Publication date: 27 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2019.1632858

zbMATH Keywords

Markov chain Monte CarloBayesian inferencediscrete probability distributionsequation-solving estimatorMetropolis-Hastings algorithm with delayed rejection

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Cites Work

• Efficient MCMC estimation of discrete distributions
• A note on Metropolis-Hastings kernels for general state spaces
• On Metropolis-Hastings algorithms with delayed rejection
• Markov chains for exploring posterior distributions. (With discussion)
• Scaling analysis of delayed rejection MCMC methods
• Delayed rejection in reversible jump Metropolis-Hastings
• On the empirical efficiency of local MCMC algorithms with pools of proposals
• Optimum Monte-Carlo sampling using Markov chains
• Equation-solving estimator based on Metropolis-Hastings algorithm with delayed rejection
• Efficient computational strategies for doubly intractable problems with applications to Bayesian social networks

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