Novel Parametric and Semiparametric Regression Models With Applications to Complete and Censored Data

Mohammed Hashim Bamba Mustapha, Dioggban Jakperik and Suleman Nasiru

Journal of Applied Mathematics, 2026, vol. 2026, 1-23

Abstract: Novel parametric and semiparametric regression models are proposed in this study based on the four-parameter tan exponentiated odd log-logistic Weibull distribution. Some statistical properties of the new distribution are derived. The parameters of the models are estimated through a maximum likelihood approach. Monte Carlo simulations for some finite parameter values and sample sizes under different censoring percentages empirically revealed the consistency of the estimators. The robustness of the proposed regression models over other regression models under the GAMLSS framework is demonstrated by means of censored and uncensored data. Thus, the new models can be viewed as intriguing alternatives for future work on real data.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnljam:6660326

DOI: 10.1155/jama/6660326

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