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Mean functions based on meta-mixtures in nonhomogeneous Poisson processes

Authors
Kim, Dae KyungPark, Dong HoYeo, In-Kwon
Issue Date
Jun-2010
Publisher
KOREAN STATISTICAL SOC
Keywords
Beta-mixtures; EM algorithm; Intensity function; Mean function
Citation
JOURNAL OF THE KOREAN STATISTICAL SOCIETY, v.39, no.2, pp.237 - 244
Journal Title
JOURNAL OF THE KOREAN STATISTICAL SOCIETY
Volume
39
Number
2
Start Page
237
End Page
244
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/13201
DOI
10.1016/j.jkss.2009.08.003
ISSN
1226-3192
Abstract
This paper deals with the software reliability model based on a nonhomogeneous Poisson process. We introduce new types of mean functions which can be either NHPP-I or NHPP-II according to the choice of the distribution function. The proposed mean function is motivated by the fact that a strictly monotone increasing function can be modeled by a distribution function and an unknown distribution function approximated by a mixture of beta distributions. Some existing mean functions can be regarded as special cases of the proposed mean functions. The EM algorithm is used to obtain maximum likelihood estimates of the parameters in the proposed model. Crown Copyright (C) 2009 Published by Elsevier B.V. on behalf of The Korean Statistical Society. All rights reserved.
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