BAYESIAN IDENTIFICATION OF MULTIPLE CHANGE POINTS IN POISSON DATA

R. H. Loschi () and F. R. B. Cruz ()
Additional contact information
R. H. Loschi: Statistics Department, Federal University of Minas Gerais, 31270-901 — Belo Horizonte — MG, Brazil
F. R. B. Cruz: Statistics Department, Federal University of Minas Gerais, 31270-901 — Belo Horizonte — MG, Brazil

Advances in Complex Systems (ACS), 2005, vol. 08, issue 04, 465-482

Abstract: The identification of multiple change points is a problem shared by many subject areas, including disease and criminality mapping, medical diagnosis, industrial control, and finance. An algorithm based on the Product Partition Model (PPM) is developed to solve the multiple change point identification problem in Poisson data sequences. In order to address the PPM, a simple and easy way to implement Gibbs sampling scheme is derived. A sensitivity analysis is performed, for different prior specifications. The algorithm is then applied to the analysis of a real data sequence. The results show that the method is quite effective and provides useful inferences.

Keywords: Beta prior distribution; student-tdistribution; Yao's cohesions; Gibbs sampling (search for similar items in EconPapers)
Date: 2005
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219525905000506
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:08:y:2005:i:04:n:s0219525905000506

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219525905000506

Access Statistics for this article

Advances in Complex Systems (ACS) is currently edited by Frank Schweitzer

More articles in Advances in Complex Systems (ACS) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().