SOME THEORETICAL AND COMPUTATIONAL ASPECTS OF THE INVERSE GENERALIZED POWER WEIBULL DISTRIBUTION

This paper introduces a new three-parameter distribution called inverse generalized power Weibull distribution. This distribution can be regarded as a reciprocal of the generalized power Weibull distribution. The new distribution is characterized by being a general formula for some well-known distri...

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Bibliographic Details
Published in:Journal of Data Science 2021-02, Vol.17 (4), p.742-755
Main Author: Selim, Mahmoud Ali
Format: Article
Language:English
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Summary:This paper introduces a new three-parameter distribution called inverse generalized power Weibull distribution. This distribution can be regarded as a reciprocal of the generalized power Weibull distribution. The new distribution is characterized by being a general formula for some well-known distributions, namely inverse Weibull, inverse exponential, inverse Rayleigh and inverse Nadarajah-Haghighi distributions. Some of the mathematical properties of the new distribution including the quantile, density, cumulative distribution functions, moments, moments generating function and order statistics are derived. The model parameters are estimated using the maximum likelihood method. The Monte Carlo simulation study is used to assess the performance of the maximum likelihood estimators in terms of mean squared errors. Two real datasets are used to demonstrate the flexibility of the new distribution as well as to demonstrate its applicability.
ISSN:1683-8602
1680-743X
1683-8602
DOI:10.6339/JDS.201910_17(4).0007