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A Bayesian change-point analysis for software reliability models

Title
A Bayesian change-point analysis for software reliability models
Authors
Nam S.Cha J.H.Cho S.
Ewha Authors
차지환
SCOPUS Author ID
차지환scopus
Issue Date
2008
Journal Title
Communications in Statistics: Simulation and Computation
ISSN
0361-0918JCR Link
Citation
vol. 37, no. 9, pp. 1855 - 1869
Indexed
SCIE; SCOPUS WOS scopus
Abstract
In most software reliability models which utilize the nonhomogeneous Poisson process (NHPP), the intensity function for the counting process is usually assumed to be continuous and monotone. However, on account of various practical reasons, there may exist some change points in the intensity function and thus the assumption of continuous and monotone intensity function may be unrealistic in many real situations. In this article, the Bayesian change-point approach using beta-mixtures for modeling the intensity function with possible change points is proposed. The hidden Markov model with non constant transition probabilities is applied to the beta-mixture for detecting the change points of the parameters. The estimation and interpretation of the model is illustrated using the Naval Tactical Data System (NTDS) data. The proposed change point model will be also compared with the competing models via marginal likelihood. It can be seen that the proposed model has the highest marginal likelihood and outperforms the competing models.
DOI
10.1080/03610910802296646
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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