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On Maximum Likelihood Estimation for a General Non-homogeneous Poisson Process

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Non-homogeneous Poisson processes (INHPPs) have been widely used in the study of software reliability. The statistical analysis for NHPPs is of interest to both theoreticians and practitioners. In this paper, maximum likelihood estimation under time-truncated sampling is studied for parametric NHPP software reliability models with bounded mean value functions. It is shown that the maximum likelihood estimators need not be consistent or asymptotically normal. The asymptotic distribution is derived for a specific NHPP model.
Original languageEnglish
Pages (from-to)597-607
JournalScandinavian Journal of Statistics
Volume23
Issue number4
Publication statusPublished - Dec 1996
Externally publishedYes

Research Keywords

  • Asymptotic distribution
  • Maximum likelihood estimation
  • Non-homogeneous Poisson process
  • Software reliability
  • Time-truncated sampling

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