Mean functions based on meta-mixtures in nonhomogeneous Poisson processes
- Authors
- Kim, Dae Kyung; Park, Dong Ho; Yeo, 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
- Pages
- 8
- 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
1876-4231
- 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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