Discretizing a Normal Prior for Change Point Estimation in Switching Regressions

Walter W. Piegorsch

doi:10.1002/bimj.4710290705

Discretizing a Normal Prior for Change Point Estimation in Switching Regressions

Walter W. Piegorsch

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Bayes decision procedures are considered for change point estimation in the simple bilinear segmented model. A discretized normal prior density is employed as the prior distribution for the change point index. Posterior probability functions are developed for this index under a vague prior formulation on the regression parameters. The procedure is applied to an example involving mercury toxicity data.

Original language	English (US)
Pages (from-to)	777-782
Number of pages	6
Journal	Biometrical Journal
Volume	29
Issue number	7
DOIs	https://doi.org/10.1002/bimj.4710290705
State	Published - 1987
Externally published	Yes

Keywords

Bayes analysis
Nonlinear regression
Segmented regression

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1002/bimj.4710290705

Cite this

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title = "Discretizing a Normal Prior for Change Point Estimation in Switching Regressions",

abstract = "Bayes decision procedures are considered for change point estimation in the simple bilinear segmented model. A discretized normal prior density is employed as the prior distribution for the change point index. Posterior probability functions are developed for this index under a vague prior formulation on the regression parameters. The procedure is applied to an example involving mercury toxicity data.",

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year = "1987",

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AB - Bayes decision procedures are considered for change point estimation in the simple bilinear segmented model. A discretized normal prior density is employed as the prior distribution for the change point index. Posterior probability functions are developed for this index under a vague prior formulation on the regression parameters. The procedure is applied to an example involving mercury toxicity data.

KW - Bayes analysis

KW - Nonlinear regression

KW - Segmented regression

UR - https://www.scopus.com/pages/publications/33645080837

UR - https://www.scopus.com/pages/publications/33645080837#tab=citedBy

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DO - 10.1002/bimj.4710290705

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EP - 782

JO - Biometrical Journal

JF - Biometrical Journal

IS - 7

ER -

Discretizing a Normal Prior for Change Point Estimation in Switching Regressions

Abstract

Keywords

ASJC Scopus subject areas

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