On computing multiple change points for the gamma distribution

Xun Xiao, Piao Chen, Zhisheng Ye, Kwok Leung Tsui

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This study proposes an efficient approach to detect one or more change points for gamma distribution. We plug a closed-form estimator into the gamma log-likelihood function to obtain a sharp approximation to the maximum of log-likelihood. We further derive a closed form calibration of approximate likelihood which is asymptotically equivalent to the exact log-likelihood. This circumvents iterative optimization procedures to find maximum likelihood estimates which can be a burden in detecting multiple change points. The simulation study shows that the approximation is accurate and the change points can be detected much faster. Two case studies on the time between events arising from industrial accidents are presented and extensively investigated.

Original languageEnglish
JournalJournal of Quality Technology
DOIs
Publication statusAccepted/In press - 1 Jan 2021
Externally publishedYes

Keywords

  • approximate likelihood
  • calibration
  • change point analysis
  • industrial accidents
  • likelihood ratio test
  • time between events

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