Designing simple and efficient Markov chain Monte Carlo proposal kernels
type: Item
instance of: scholarly article
title: Designing simple and efficient Markov chain Monte Carlo proposal kernels
zbMATH Open document ID: 1407.60103
DOI: 10.1214/17-BA1084
author: Yuttapong Thawornwattana
author: Daniel Dalquen
author: Ziheng Yang
published in: Bayesian Analysis
publication date: 2018-12-06T00:00:00Z
full work available at URL: https://projecteuclid.org/euclid.ba/1510282998
Mathematics Subject Classification ID: 60J22
Mathematics Subject Classification ID: 65C05
zbMATH DE Number: 6989975
zbMATH Keywords: asymptotic variance
zbMATH Keywords: bimodal kernel
zbMATH Keywords: Metropolis-Hastings algorithm
zbMATH Keywords: mirror kernel
zbMATH Keywords: molecular clock dating
zbMATH Keywords: variable transformation
zbMATH Keywords: design
zbMATH Keywords: logistic regression problem
describes a project that uses: Stan
describes a project that uses: NUTS
MaRDI profile type: Publication
cites work: Improving Stochastic Relaxation for Gussian Random Fields
cites work: Scaling analysis of multiple-try MCMC methods
cites work: Scaling analysis of delayed rejection MCMC methods
cites work: Optimal tuning of the hybrid Monte Carlo algorithm
cites work: Optimal scalings for local Metropolis-Hastings chains on nonproduct targets in high dimensions
cites work: MCMC algorithms for constrained variance matrices
cites work: Q3723577
cites work: Antithetic coupling of two Gibbs sampler chains.
cites work: Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
cites work: Q3234488
cites work: Monte Carlo sampling methods using Markov chains and their applications
cites work: The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
cites work: Q3262596
cites work: Equation of State Calculations by Fast Computing Machines
cites work: Efficiency of finite state space Monte Carlo Markov chains
cites work: Q3405572
cites work: Optimum Monte-Carlo sampling using Markov chains
cites work: Optimal scaling and diffusion limits for the Langevin algorithm in high dimensions
cites work: Weak convergence and optimal scaling of random walk Metropolis algorithms
cites work: Optimal Scaling of Discrete Approximations to Langevin Diffusions
cites work: Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets
cites work: Markov chains for exploring posterior distributions. (With discussion)
cites work: A note on Metropolis-Hastings kernels for general state spaces
cites work: Searching for efficient Markov chain Monte Carlo proposal kernels
OpenAlex ID: W2767866961
description: scientific article; zbMATH DE number 6989975