A Simple Extension of Burr-III Distribution and Its Advantages over Existing Ones in Modelling Failure Time Data
Subrata Chakraborty (subrata_stats@dibru.ac.in),
Laba Handique (handiquelaba@gmail.com) and
Rana Muhammad Usman (usmanrana0331@gmail.com)
Additional contact information
Subrata Chakraborty: Dibrugarh University
Laba Handique: Dibrugarh University
Rana Muhammad Usman: University of the Punjab
Annals of Data Science, 2020, vol. 7, issue 1, No 2, 17-31
Abstract:
Abstract In this article we consider a four parameter extended Burr-III distribution and study some distributional, reliability properties and parameter estimation. Performance of estimation technique used for model parameters estimation is numerically investigated employing Monte Carlo simulation with different sample sizes and parameter values. Efficacy of this distribution in modelling one failure time data is evaluated in comparison to some existing extensions of Bur-III distribution employing well known goodness of fit tests and model selection criteria. Our findings show the proposed distribution as the best among the all the other extensions of Burr-III distribution considered in this study.
Keywords: Exponentiated family; Burr-III distribution; Maximum likelihood; K–S test; LR test; 60E05; 62G05; 62G20 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:aodasc:v:7:y:2020:i:1:d:10.1007_s40745-019-00227-2
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DOI: 10.1007/s40745-019-00227-2
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