On the estimation problems for discrete inverse gamma lifetime model with real data applications

Inverse gamma distribution is one of the most useful distributions for attempting various physical world problems. In this work, its discretized form, namely, discrete inverse gamma distribution has been explored as a suitable lifetime model for analyzing the discrete lifetime data in various real-w...

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Bibliographic Details
Published inLife cycle reliability and safety engineering Vol. 11; no. 4; pp. 313 - 321
Main Authors Pundir, Pramendra Singh, Srivastava, Rachna, Agarwal, S. K., Shrivastava, Vikas
Format Journal Article
LanguageEnglish
Published Singapore Springer Nature Singapore 01.12.2022
Subjects
Civil Engineering
Engineering
Mechanical Engineering
Original Research
Quality Control
Reliability
Safety and Risk
Bootstrapping
Bayes estimation
Reversed second rate of failure
ML estimation
Discrete inverse gamma distribution
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Summary:Inverse gamma distribution is one of the most useful distributions for attempting various physical world problems. In this work, its discretized form, namely, discrete inverse gamma distribution has been explored as a suitable lifetime model for analyzing the discrete lifetime data in various real-world situations. Some of its reliability characteristics have been presented in this work. Classical and Bayesian estimators of unknown parameters have also been obtained along with their respective asymptotic confidence intervals, percentile bootstrap confidence intervals, bootstrap-t confidence intervals and highest posterior density intervals. A detailed table of simulated results elicits the effectiveness of the proposed theory. The applicability of the model has been exhibited through real-life datasets.
ISSN:2520-1352
2520-1360
DOI:10.1007/s41872-022-00204-4