Calculating the content and boundary of the highest posterior density region via data augmentation

Greg C G Wei; Martin A. Tanner

doi:10.1093/biomet/77.3.649

Calculating the content and boundary of the highest posterior density region via data augmentation

Greg C G Wei^*, Martin A. Tanner

^*Corresponding author for this work

Statistics and Data Science

Research output: Contribution to journal › Comment/debate › peer-review

26 Scopus citations

Abstract

This note considers the computation of the content and the boundary of the highest posterior density region in the context of data augmentation. The notion of the highest posterior density region and the data augmentation algorithm are reviewed. The sampling-based approach for calculating the content and the boundary of the highest posterior density region is then presented. The method is illustrated in the context of right-censored regression data.

Original language	English (US)
Pages (from-to)	649-652
Number of pages	4
Journal	Biometrika
Volume	77
Issue number	3
DOIs	https://doi.org/10.1093/biomet/77.3.649
State	Published - Sep 1 1990

Keywords

Bayesian inference
Censored data
Missing data
Multiple imputation
Simulation

ASJC Scopus subject areas

Statistics and Probability
General Mathematics
Agricultural and Biological Sciences (miscellaneous)
General Agricultural and Biological Sciences
Statistics, Probability and Uncertainty
Applied Mathematics

Access to Document

10.1093/biomet/77.3.649

Cite this

@article{8bb1d6a91374490097c826f246f1761c,

title = "Calculating the content and boundary of the highest posterior density region via data augmentation",

abstract = "This note considers the computation of the content and the boundary of the highest posterior density region in the context of data augmentation. The notion of the highest posterior density region and the data augmentation algorithm are reviewed. The sampling-based approach for calculating the content and the boundary of the highest posterior density region is then presented. The method is illustrated in the context of right-censored regression data.",

keywords = "Bayesian inference, Censored data, Missing data, Multiple imputation, Simulation",

author = "Wei, {Greg C G} and Tanner, {Martin A.}",

year = "1990",

month = sep,

day = "1",

doi = "10.1093/biomet/77.3.649",

language = "English (US)",

volume = "77",

pages = "649--652",

journal = "Biometrika",

issn = "0006-3444",

publisher = "Oxford University Press",

number = "3",

}

TY - JOUR

T1 - Calculating the content and boundary of the highest posterior density region via data augmentation

AU - Wei, Greg C G

AU - Tanner, Martin A.

PY - 1990/9/1

Y1 - 1990/9/1

N2 - This note considers the computation of the content and the boundary of the highest posterior density region in the context of data augmentation. The notion of the highest posterior density region and the data augmentation algorithm are reviewed. The sampling-based approach for calculating the content and the boundary of the highest posterior density region is then presented. The method is illustrated in the context of right-censored regression data.

AB - This note considers the computation of the content and the boundary of the highest posterior density region in the context of data augmentation. The notion of the highest posterior density region and the data augmentation algorithm are reviewed. The sampling-based approach for calculating the content and the boundary of the highest posterior density region is then presented. The method is illustrated in the context of right-censored regression data.

KW - Bayesian inference

KW - Censored data

KW - Missing data

KW - Multiple imputation

KW - Simulation

UR - http://www.scopus.com/inward/record.url?scp=0000242257&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0000242257&partnerID=8YFLogxK

U2 - 10.1093/biomet/77.3.649

DO - 10.1093/biomet/77.3.649

M3 - Comment/debate

AN - SCOPUS:0000242257

SN - 0006-3444

VL - 77

SP - 649

EP - 652

JO - Biometrika

JF - Biometrika

IS - 3

ER -

Calculating the content and boundary of the highest posterior density region via data augmentation

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this