TY - JOUR
TI - Bayesian and non-Bayesian estimation methods to independent competing risks models with type II half logistic weibull sub-distributions with application to an automatic life test
AU - Tolba Ahlam H
AU - Almetwally Ehab M
AU - Sayed-Ahmed Neveen
AU - Jawa Taghreed M
AU - Yehia Nagla
AU - Ramadan Dina A
JN - Thermal Science
PY - 2022
VL - 26
IS - 101
SP - 285
EP - 302
PT - Article
AB - In the survival data analysis, competing risks are commonly overlooked, and  conventional statistical methods are used to analyze the event of interest.  There may be more than one cause of death or failure in many experimental  investigations of survival analysis. A competing risks model will be derived  statistically applying Type-II half logistic weibull sub-distributions.  Type-II half logistic weibull life­times failure model with independent  causes. It is possible to estimate parameters and parametric functions using  Bayesian and classical methods. A Bayes estimation is obtained by the  Markov chain Monte-Carlo method. The posterior density function and the  Metropolis-Hasting algorithm are used to calculate the Markov chain  Monte-Carlo samples. Simulation data is used to evaluate the performance of  the two methods according to the Type-II censored system. As a test of the  discussed model, a real data set is provided.