English, Article edition: APPLYING THE PRODUCT PARTITION MODEL TO THE IDENTIFICATION OF MULTIPLE CHANGE POINTS R. H. LOSCHI; F. R. B. CRUZ

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Physical Description
  • article
Language
  • English

Edition details

Title
  • APPLYING THE PRODUCT PARTITION MODEL TO THE IDENTIFICATION OF MULTIPLE CHANGE POINTS
Author
  • R. H. LOSCHI
  • F. R. B. CRUZ
Physical Description
  • article
Notes
  • The multiple change point identification problem may be encountered in many subject areas, including disease mapping, medical diagnosis, industrial control, and finance. One appealing way of tackling the problem is through the product partition model (PPM), a Bayesian approach. Nowadays, practical applications of Bayesian methods have attracted attention perhaps because of the generalized use of powerful and inexpensive personal computers. A Gibbs sampling scheme, simple and easy to implement, is used to obtain the estimates. We apply the algorithm to the analysis of two important stock market data in Brazil. The results show that the method is efficient and effective in analyzing change point problems.
  • Beta prior distribution, relevance, Student-t distribution, Yao's cohesions
  • RePEc:wsi:acsxxx:v:05:y:2002:i:04:p:371-387
Language
  • English
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