Statistical Inference to the Parameter of the Akshaya Distribution under Competing Risks Data with Application HIV Infection to AIDS

Dina A. Ramadan (), Ehab M. Almetwally () and Ahlam H. Tolba ()
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Dina A. Ramadan: Mansoura University
Ehab M. Almetwally: Delta University for Science and Technology
Ahlam H. Tolba: Mansoura University

Annals of Data Science, 2023, vol. 10, issue 6, No 4, 1499-1525

Abstract: Abstract This paper takes into consideration statistical inferences in competing risk models with Akshaya sub-distributions based on the type-II censoring scheme. It is supposed to be the k causes of failures. In the analysis of point and interval estimations of all model parameters, maximum likelihood and Bayesian procedures are applied. The Gibbs within Metropolis–Hasting samplers procedure is applied using the Markov chain Monte Carlo (MCMC) technique to get the Bayes estimates of the unknown parameters, their credible intervals (CRIs) and to estimate the relative risks. Furthermore, the survivor functions for subsystems and the overall system are evaluated. Finally, a real-life data set, which represents the times (in years) from HIV infection to AIDS and death in 329 men who had sex with men (MSM), is considered an application of the proposed methods.

Keywords: Causes of failures; Akshaya distribution; Bayesian method; Reliability analysis; Markov chain Monte Carlo; Relative risks; HIV infection (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s40745-022-00382-z

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