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Bayesian Estimation of change points using the general linear model
Author(s) -
Rasmussen Peter
Publication year - 2001
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2001wr000311
Subject(s) - bayesian probability , bayesian linear regression , linear model , point estimation , general linear model , computer science , bayes estimator , econometrics , point (geometry) , change detection , basis (linear algebra) , mathematics , statistics , posterior probability , bayesian inference , artificial intelligence , geometry
Bayesian analysis is applied to the general linear model to develop a framework for studying different types of change in the mean value of time series and linear regressions. The output of the Bayesian analysis is the posterior distribution of change point location and amplitude. This information provides a rational and relatively objective basis for making decisions as to where to locate a change point. Several examples of hydrological applications are presented to demonstrate the utility of the methodology.