Unconditional tests of goodness of fit for the intensity of time-truncated nonhomogeneous Poisson processes

Madhuchhanda Bhattacharjee, J V Deshpande, U V Naik-Nimbalkar

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Procedures for testing trends in the intensity functions of nonhomogeneous Poisson processes are based mostly on conditioning on the number of failures observed in (0. t] with fixed t. We study an unconditional test based on the time-truncated data that enables meaningful asymptotics as t --> infinity. We show that the asymptotic test is conservative and that its power quickly comes close to the power of the uniformly most powerful unbiased test for the power-law alternatives. Moreover, for the goodness of fit of a specified intensity, the exact test has more power than the test based on the conditional approach. We illustrate the procedure using a real dataset.

Original languageEnglish
Pages (from-to)330-338
Number of pages9
JournalTechnometrics
Volume46
Issue number3
DOIs
Publication statusPublished - Aug 2004

Keywords

  • asymptotic relative efficiency
  • consistency
  • intensity function
  • minimal-repair
  • nonhomogeneous
  • Poisson process
  • trend testing
  • PROPORTIONAL HAZARDS
  • MODEL

Fingerprint

Dive into the research topics of 'Unconditional tests of goodness of fit for the intensity of time-truncated nonhomogeneous Poisson processes'. Together they form a unique fingerprint.

Cite this