Mean functions based on meta-mixtures in nonhomogeneous Poisson processes

  • Dae Kyung Kim
  • , Dong Ho Park
  • , In Kwon Yeo*
  • *Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

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

Original languageEnglish
Pages (from-to)237-244
Number of pages8
JournalJournal of the Korean Statistical Society
Volume39
Issue number2
DOIs
StatePublished - 2010.06

Keywords

  • Beta-mixtures
  • EM algorithm
  • Intensity function
  • Mean function

Quacquarelli Symonds(QS) Subject Topics

  • Mathematics
  • Statistics & Operational Research
  • Data Science

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