A New Generalized Family of Weibull-Exponentiated Half Logistic-G Distribution with Applications

We propose a new extension of the Weibull-exponentiated half logistic-G (WEHL-G) distribution, called the Marshall-Olkin-Weibull-exponentiated half logistic-G (MO-WEHL-G) family of distributions. The properties of this family of distributions including quantile function, distribution of the order statistics, hazard rate function, Rényi entropy and moments of residual life are presented. To estimate the parameters of the MO-WEHL-G family of distributions, six different estimation approaches are used, namely, maximum likelihood, Anderson-Darling, Ordinary Least Squares, Weighted Least Squares, Cramér-von Mises and Maximum Product of Spacing. The consistency properties of the six estimation methods were assessed using Monte Carlo simulations for a special case of the MO-WEHL-G family of distributions. The flexibility and importance of the proposed model was assessed using numerous goodness-of-fit statistics on three different data sets.

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Publication Details

Journal
Central European Journal of Economic Modelling and Econometrics
Published
2024-10-28
DOI
https://doi.org/10.24425/cejeme.2024.152688
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

A New Generalized Family of Weibull-Exponentiated Half Logistic-G Distribution with Applications

Gayan Warahena-Liyanage, Broderick Olusegun Oluyede, Thatayaone Moakofi, Agolame Puoetsile
Central European Journal of Economic Modelling and Econometrics
Statistical Distribution Estimation and Applications
article

A New Generalized Family of Weibull-Exponentiated Half Logistic-G Distribution with Applications

Gayan Warahena-Liyanage, Broderick Olusegun Oluyede, Thatayaone Moakofi, Agolame Puoetsile
article en

Abstract

We propose a new extension of the Weibull-exponentiated half logistic-G (WEHL-G) distribution, called the Marshall-Olkin-Weibull-exponentiated half logistic-G (MO-WEHL-G) family of distributions. The properties of this family of distributions including quantile function, distribution of the order statistics, hazard rate function, Rényi entropy and moments of residual life are presented. To estimate the parameters of the MO-WEHL-G family of distributions, six different estimation approaches are used, namely, maximum likelihood, Anderson-Darling, Ordinary Least Squares, Weighted Least Squares, Cramér-von Mises and Maximum Product of Spacing. The consistency properties of the six estimation methods were assessed using Monte Carlo simulations for a special case of the MO-WEHL-G family of distributions. The flexibility and importance of the proposed model was assessed using numerous goodness-of-fit statistics on three different data sets.

Central European Journal of Economic Modelling and Econometrics
University of Dayton (US), Botswana International University of Science and Technology (BW)
Openalex Percentile: Top 81%
Statistical Distribution Estimation and Applications
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