Efficient Metropolis-Hastings proposal mechanisms for Bayesian regression tree models comment

A. Mohammadi; M.C. Kaptein

Efficient Metropolis-Hastings proposal mechanisms for Bayesian regression tree models comment

Methodology and Statistics

Research output: Contribution to journal › Editorial › Scientific › peer-review

Abstract

The author should be commended for his outstanding contribution to the literature on Bayesian regression tree models. The author introduces three innovative sampling approaches which allow for efficient traversal of the model space. In this response, we add a fourth alternative.

Original language	English
Pages (from-to)	938-940
Journal	Bayesian Analysis
Volume	11
Issue number	3
Publication status	Published - Sept 2016

Keywords

Markov chain Monte Carlo
birth-death process
continuous time Markov process
Bayesian regression tree
REVERSIBLE JUMP
MIXTURE

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title = "Efficient Metropolis-Hastings proposal mechanisms for Bayesian regression tree models comment",

abstract = "The author should be commended for his outstanding contribution to the literature on Bayesian regression tree models. The author introduces three innovative sampling approaches which allow for efficient traversal of the model space. In this response, we add a fourth alternative.",

keywords = "Markov chain Monte Carlo, birth-death process, continuous time Markov process, Bayesian regression tree, REVERSIBLE JUMP, MIXTURE",

author = "A. Mohammadi and M.C. Kaptein",

year = "2016",

month = sep,

language = "English",

volume = "11",

pages = "938--940",

journal = "Bayesian Analysis",

issn = "1931-6690",

publisher = "INT SOC BAYESIAN ANALYSIS",

number = "3",

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TY - JOUR

T1 - Efficient Metropolis-Hastings proposal mechanisms for Bayesian regression tree models comment

AU - Mohammadi, A.

AU - Kaptein, M.C.

PY - 2016/9

Y1 - 2016/9

N2 - The author should be commended for his outstanding contribution to the literature on Bayesian regression tree models. The author introduces three innovative sampling approaches which allow for efficient traversal of the model space. In this response, we add a fourth alternative.

AB - The author should be commended for his outstanding contribution to the literature on Bayesian regression tree models. The author introduces three innovative sampling approaches which allow for efficient traversal of the model space. In this response, we add a fourth alternative.

KW - Markov chain Monte Carlo

KW - birth-death process

KW - continuous time Markov process

KW - Bayesian regression tree

KW - REVERSIBLE JUMP

KW - MIXTURE

M3 - Editorial

SN - 1931-6690

VL - 11

SP - 938

EP - 940

JO - Bayesian Analysis

JF - Bayesian Analysis

IS - 3

ER -

Efficient Metropolis-Hastings proposal mechanisms for Bayesian regression tree models comment

Abstract

Keywords

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