Bayesian analysis for detecting a change in exponential family

Ghorbanzadeh, Dariush; Lounes, Rachid

doi:10.1016/s0096-3003(00)00029-1

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…Simulation has been used to study the effect of a single outlier on the Bayesian significance test based on the highest posterior density credible set (Kim, 1991;Ghorbanzadeh and Lounes, 2001). …”

Section: Simulation Studymentioning

confidence: 99%

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A Bayesian significance test of change in the presence of a single outlier

Slama¹

2014

jas

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Abstract. The Bayesian significance test for a change in independent gaussian samples in the presence of single outlier is considered. The impact of an outlier on the performance of the Bayesian significance test is studied.Résumé. Dans ce travail, nous considérons un test de signification Bayésien pour la détection de rupture dans unéchantillon gaussien en présence d'une observation aberrante. L'impact d'une contamonation sur la performance du test estétudié.

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Section: Simulation Studymentioning

confidence: 99%

“…Ghorbanzadeh and Lounes (2001) proposed a Bayesian analysis of detection of a change of parameters in a sequence of independent random variables from an exponential family.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian significance test of change in the presence of a single outlier

Slama¹

2014

jas

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“…The technique used in this work is the normal case of a general changepoint technique which allows the detection of a change in the parameter of a distribution belonging to the natural exponential family (Lee, 1998). This problem has also been addressed in the Bayesian framework by Kander and Zacks (1966), Smith (1975) and Ghorbanzadeh and Lounes (2001). However, the approach of Lee (1998) was used because it is the most recent presenting the special case of a changepoint detection in the mean of a normally distributed time series, which is the case of interest in this paper.…”

Section: Description Of the Techniquementioning

confidence: 99%

“…The above prior distributions for the changepoint position were proposed because they lead to analytical expression for the posterior distribution and they can easily be used to integrate metadata in the analysis. Some examples of alternative prior distributions can be found in Ghorbanzadeh and Lounes (2001).…”

Section: Description Of the Techniquementioning

confidence: 99%

A Bayesian normal homogeneity test for the detection of artificial discontinuities in climatic series

Beaulieu¹,

Ouarda²,

Seidou³

2010

Intl Journal of Climatology

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A Bayesian Normal Homogeneity Test (BNHT) for the detection of artificial discontinuities in climatic series is presented. The test is simple to use and allows the integration of prior knowledge on the date of change from various sources of information (e.g. metadata or expert belief) in the analysis. The performance of the new test was evaluated on synthetic series with similar statistical properties as observed total annual precipitation in the southern and central parts of the province of Quebec, Canada. Different priors were used to investigate the sensitivity of the test to the choice of priors. It was found that (1) high-prior probability of no change yields low false detection rates on the homogeneous series; (2) the test has a very high power of detection on series with a single shift (the best power of detection if compared with previous methods applied to the same synthetic series); (3) shifts having a small magnitude are detectable with a low prior probability of no change and (4) when applied to series with multiple shifts with a segmentation procedure and a high probability of no change, the test proved to be performing well in detecting multiple shifts (as performing as the best techniques previously applied to the same synthetic series). An example of application to total annual precipitation in Quebec City, Canada is also presented to illustrate (1) a case for which the results are not affected by the choice of the prior parameters and (2) a case for which information about potential changes found in the metadata was integrated in the analysis and allowed the detection of a change that would not have been detected with a non-informative prior.

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“…He also discussed interval estimation for the changepoint. Ghorbanzadeh and Lounes (2001) carried out a Bayesian analysis to detect a change in an exponential family. More recently, Wu (2005) has written a book about CUSUM 9 tests for changepoint problems with emphasis on exponential families.…”

Section: Changepoint Problemsmentioning

confidence: 99%

Bayesian optimal design for changepoint problems

et al. 2009

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We investigate Bayesian optimal designs for changepoint problems. We find robust optimal designs which allow for arbitrary distributions before and after the change, arbitrary prior densities on the parameters before and after the change, and any log‐concave prior density on the changepoint. We define a new design measure for Bayesian optimal design problems as a means of finding the optimal design. Our results apply to any design criterion function concave in the design measure. We illustrate our results by finding the optimal design in a problem motivated by a previous clinical trial. The Canadian Journal of Statistics 37: 495–513; 2009 © 2009 Statistical Society of Canada

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Bayesian analysis for detecting a change in exponential family

Abstract: We propose a Bayesian analysis of detection of a change of parameter in a sequence of independent random variables from exponential family. The test uses the highest posterior density credible set. Ó

Cited by 5 publications

References 11 publications

A Bayesian significance test of change in the presence of a single outlier

A Bayesian significance test of change in the presence of a single outlier

A Bayesian normal homogeneity test for the detection of artificial discontinuities in climatic series

Bayesian optimal design for changepoint problems

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