2020Unpublished venueRequires access

A new power generalized Weibull-G family of distributions: Properties and applications

Broderick O. Oluyede, Thatayaone Moakofi, Fastel Chipepa, Boikanyo Makubate

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Abstract

‎A new family of continuous distributions namely‎ ‎new power generalized Weibull-G family of distributions is proposed‎. ‎Some special sub-models of the new family are provided‎. ‎Some statistical properties of the new family of distributions are obtained including the quantile function‎, ‎ordinary and incomplete moments‎, ‎probability weighted moments‎, ‎distribution of the order statistics and Renyi entropy‎. ‎The maximum likelihood method is used for estimating model parameters‎. ‎A simulation study is employed to check the consistency of the maximum likelihood estimates‎. ‎The flexibility of a sub-model of the generated family is illustrated by means of two applications to real data sets.

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What this paper is about

‎A new family of continuous distributions namely‎ ‎new power generalized Weibull-G family of distributions is proposed‎. ‎Some special sub-models of the new family are provided‎. ‎Some statistical properties of the new family of distributions are obtained including the quantile function‎, ‎ordinary and incomplete moments‎, ‎probability weighted moments‎, ‎distribution of the order statistics and Renyi entropy‎. ‎The maximum likelihood method is used for estimating model parameters‎. ‎A simulation study is employed to check the consistency of the maximum likelihood estimates‎. ‎The flexibility of a sub-model of the generated family is illustrated by means of two applications to real data sets.

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Available abstract

‎A new family of continuous distributions namely‎ ‎new power generalized Weibull-G family of distributions is proposed‎. ‎Some special sub-models of the new family are provided‎. ‎Some statistical properties of the new family of distributions are obtained including the quantile function‎, ‎ordinary and incomplete moments‎, ‎probability weighted moments‎, ‎distribution of the order statistics and Renyi entropy‎. ‎The maximum likelihood method is used for estimating model parameters‎. ‎A simulation study is employed to check the consistency of the maximum likelihood estimates‎. ‎The flexibility of a sub-model of the generated family is illustrated by means of two applications to real data sets.

Key concepts: Quantile function, Mathematics, Weibull distribution, Quantile, Order statistic, K-distribution, Natural exponential family, Statistics

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