Modified information criteria for selecting a finite mixture model
Joint Authors
Kazim, Safa Khidr
Daham, Hajim A.
Source
Muthanna Journal of Administrative and Economic Sciences
Issue
Vol. 10, Issue 2 (30 Jun. 2020), pp.136-152, 17 p.
Publisher
Al-Muthanna University Administration and Economics College
Publication Date
2020-06-30
Country of Publication
Iraq
No. of Pages
17
Main Subjects
Abstract EN
Recently, a paper published by Celeux et al.
(2006) presented several forms for the deviation information criterion (DIC) for mixture models, each version is depended on the kind of probability function.
However, no reliable version was adopted for those models.
As an idea inspired by Brooks (2002, p.
617), we develop, in this paper, Bayesian deviations plugging into two known criteria: the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for choosing best mix model.
Due to unavailability the closed-form of the perceived likelihood of those models, we propose an algorithm for estimating the observed likelihood for mixture models via an Markov chain Monte Carlo (MCMC) approach.
It is shown via recreation researches and examples include actual information applications that proposed AIC and BIC perform well
American Psychological Association (APA)
Kazim, Safa Khidr& Daham, Hajim A.. 2020. Modified information criteria for selecting a finite mixture model. Muthanna Journal of Administrative and Economic Sciences،Vol. 10, no. 2, pp.136-152.
https://search.emarefa.net/detail/BIM-1263038
Modern Language Association (MLA)
Kazim, Safa Khidr& Daham, Hajim A.. Modified information criteria for selecting a finite mixture model. Muthanna Journal of Administrative and Economic Sciences Vol. 10, no. 2 (2020), pp.136-152.
https://search.emarefa.net/detail/BIM-1263038
American Medical Association (AMA)
Kazim, Safa Khidr& Daham, Hajim A.. Modified information criteria for selecting a finite mixture model. Muthanna Journal of Administrative and Economic Sciences. 2020. Vol. 10, no. 2, pp.136-152.
https://search.emarefa.net/detail/BIM-1263038
Data Type
Journal Articles
Language
English
Notes
-
Record ID
BIM-1263038