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All Journal Sigma&Mu: Journal of Mathematics, Statistics and Data Science
Umar Yusuf Madaki
1Department of Mathematics and Statistics, Faculty of Science, Yobe State University, Damaturu, Nigeria
Education Mathematics

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Cured Fraction Models on Survival Data and Covariates with a Bayesian Parametric Estimation Methods Umar Yusuf Madaki; Babangida Ibrahim Babura; Muhammad Sani; Ibrahim Abdullahi
Sigma&Mu: Journal of Mathematics, Statistics and Data Science Vol. 1 No. 1 (2023): March
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/sigmamu.v1i1.45

Abstract

A cure fraction models are usually meant for survival data that contains a proportion of non subject individuals for the event under study. In order to estimate the cure fraction, two models namely mixture model and non-mixture model were commonly deployed. In this work, mixture and non-mixture cure fraction models were presented with survival data structure based on the beta-Weibull distribution. The beta-Weibull distribution is a four parameter distribution developed in this work as an alternative extension to the Weibull distribution in the analysis of lifetime data. The proposed extension allows the inclusion of covariates analysis in the model, in which the estimation of parameters were done under Bayesian approach using Gibbs sampling methods
Co-Authors Babangida Ibrahim Babura Ibrahim Abdullahi Muhammad Sani