Mean functions based on meta-mixtures in nonhomogeneous Poisson processes

被引:0
作者
Dae Kyung Kim
Dong Ho Park
In-Kwon Yeo
机构
[1] Chonbuk National University,Department of Statistical Informatics
[2] Hallym University,Department of Information and Statistics
[3] Sookmyung Women’s University,DepartmentofStatistics
来源
Journal of the Korean Statistical Society | 2010年 / 39卷
关键词
primary 60G51; secondary 62P30; Beta-mixtures; EM algorithm; Intensity function; Mean function;
D O I
暂无
中图分类号
学科分类号
摘要
This paper deals with the software reliability model based on a non homogeneous 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.
引用
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页码:237 / 244
页数:7
相关论文
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