This paper presents a Bayesian significance test for a change in mean when observations are not independent. Using a noninformative prior, a unconditional test based on the highest posterior density credible set is determined. From a Gibbs sampler simulation study the effect of correlation on the performance of the Bayesian significance test derived under the assumption of no correlation is examined. This paper is a generalization of earlier studies by KIM (1991) to not independent observations.
@article{bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1169,
author = {Abdeldjalil Slama},
title = {A Bayesian significance test of change for correlated observations},
journal = {Discussiones Mathematicae Probability and Statistics},
volume = {34},
year = {2014},
pages = {51-62},
zbl = {1326.62194},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1169}
}
Abdeldjalil Slama. A Bayesian significance test of change for correlated observations. Discussiones Mathematicae Probability and Statistics, Tome 34 (2014) pp. 51-62. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1169/
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