On alternative q-Weibull and q-extreme value distributions: Properties and applications

Fode Zhang, Hon Keung Tony Ng and Yimin Shi

Physica A: Statistical Mechanics and its Applications, 2018, vol. 490, issue C, 1171-1190

Abstract: Tsallis statistics and Tsallis distributions have been attracting a significant amount of research work in recent years. Importantly, the Tsallis statistics, q-distributions have been applied in different disciplines. Yet, a relationship between some existing q-Weibull distributions and q-extreme value distributions that is parallel to the well-established relationship between the conventional Weibull and extreme value distributions through a logarithmic transformation has not be established. In this paper, we proposed an alternative q-Weibull distribution that leads to a q-extreme value distribution via the q-logarithm transformation. Some important properties of the proposed q-Weibull and q-extreme value distributions are studied. Maximum likelihood and least squares estimation methods are used to estimate the parameters of q-Weibull distribution and their performances are investigated through a Monte Carlo simulation study. The methodologies and the usefulness of the proposed distributions are illustrated by fitting the 2014 traffic fatalities data from The National Highway Traffic Safety Administration.

Keywords: Tsallis statistics; Aq-Weibull distribution; Logarithmic transformation; q-extreme value distribution; Reliability analysis (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:490:y:2018:i:c:p:1171-1190

DOI: 10.1016/j.physa.2017.09.009

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