Please use this identifier to cite or link to this item: https://doi.org/10.1080/00224065.2020.1717398
Title: On Computing Multiple Change Points for the Gamma Distribution
Authors: Xun Xiao
PIAO CHEN 
Zhi-sheng Ye 
Kwok Leung Tsui
Keywords: approximate likelihood
calibration
change point analysis
industrial accidents
likelihood ratio test
time between events
Issue Date: 2-Mar-2020
Publisher: Taylor & Francis
Citation: Xun Xiao, PIAO CHEN, Zhi-sheng Ye, Kwok Leung Tsui (2020-03-02). On Computing Multiple Change Points for the Gamma Distribution. Journal of Quality Technology 53 (3) : 267-288. ScholarBank@NUS Repository. https://doi.org/10.1080/00224065.2020.1717398
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.
Source Title: Journal of Quality Technology
URI: https://scholarbank.nus.edu.sg/handle/10635/196009
ISSN: 00224065
DOI: 10.1080/00224065.2020.1717398
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