Kumaraswamy family of generalized Type II Exponentiated Half Logistic-G distribution: properties and statistical inference

Fastel Chipepa; Wilbert Nkomo; Nyika Mtemeri; Takesure Nyakuamba

doi:https://doi.org/10.59139/stattrans-2026-030

Kumaraswamy family of generalized Type II Exponentiated Half Logistic-G distribution: properties and statistical inference

Fastel Chipepa Botswana International University of Science and Technology, Botswana ORCID:https://orcid.org/0000-0001-6854-8740 , Wilbert Nkomo Manicaland State University of Applied Sciences, Zimbabwe & Botswana International University of Science and Technology, Botswana ORCID:https://orcid.org/0009-0006-0277-3981 , Nyika Mtemeri Avance Clinical, Firle South Australia, Australia ORCID:https://orcid.org/0000-0003-4792-8757 , Takesure Nyakuamba Manicaland State University of Applied Sciences, Zimbabwe ORCID:https://orcid.org/0009-0009-1682-0306 Statistics in Transition new series, vol. 27, 2026, 3, pages: 113-134 Published online: 9 September 2026 https://doi.org/10.59139/stattrans-2026-030 Citation: Chipepa F., Nkomo W., Mtemeri N., Nyakuamba T., 2026. Takesure Nyakuamba entitled Kumaraswamy family of generalized Type II Expo-nentiated Half Logistic-G distribution: properties and statistical inference. Statistics in Transition new series, 27(3), pp. 113-134. https://doi.org/10.59139/stattrans-2026-030

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ABSTRACT

We present a new family of distributions (FDs) named the Kumaraswamy type II exponentiated half logistic-G (K-TIIEHL-G). Notably, this FDs can be represented as an infinite linear combination of exponentiated-G densities enabling the derivation of important statistical properties. The density and hazard rate geometries were investigated for some special cases. The model parameters were determined using the maximum likelihood technique and Monte Carlo simulation experiments were carried out to validate the consistency of the model parameters. The Kumaraswamy type II exponentiated half logistic-Weibull (K-TIIEHL-W), a member of the K-TIIEHL-G family, was applied to two sets of real data. The results indicated that the K-TIIEHL-W model significantly outperformed several established contending equi-parameter models in terms of data fitting.

KEYWORDS

Kumaraswamy-G, Type II Exponentiated Half logistic-G, Exponentiated-G, Maximum Likelihood Estimation, Monte Carlo Simulations

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