A Comparison of Some Recent Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments [PDF]
We compare the finite sample performance of a number of Bayesian and classical procedures for limited information simultaneous equations models with weak instruments by a Monte Carlo study.
Chuanming Gao, Kajal Lahiri
core
Metropolis-Hastings Algorithms based on a Zero-inflated Poisson Model [PDF]
Yaoyu Chen
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A Bayesian approach to parameter estimation for kernel density estimation via transformations [PDF]
In this paper, we present a Markov chain Monte Carlo (MCMC) simulation algorithm for estimating parameters in the kernel density estimation of bivariate insurance claim data via transformations.
David Pitt +3 more
core
Metropolis-Hastings Expectation Maximization Algorithm for Incomplete Data [PDF]
, 2012 Sooyoung Cheon, Hee-Chan Lee
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Robust random walk-like Metropolis-Hastings algorithms for concentrating posteriors [PDF]
, 2022 Daniel Rudolf, Björn Sprungk
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Variance bounds and robust tuning for pseudo-marginal Metropolis--Hastings algorithms [PDF]
Chris Sherlock
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Water Resources ResearchThis discussion is a reply to the comments made by Dr. Jasper Vrugt on the Metropolis‐Hastings (M‐H) algorithm with multiple independent Markov chains proposed by Huang and Merwade (2023a), https://doi.org/10.1029/2023wr034947 concerning the validity of ...
Tao Huang, Venkatesh Merwade
doaj +1 more source
Parameter Estimation for a Gas Lifting Oil Well Model Using Bayes' Rule and the Metropolis–Hastings Algorithm [PDF]
, 2022 Zhe Ban +3 more
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Does waste-recycling really improve Metropolis-Hastings Monte Carlo algorithm? [PDF]
, 2006 Jean‐François Delmas +1 more
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