Copula Approach for Dependent Competing Risks of Generalized Half-Logistic Distributions under Accelerated Censoring Data

In medicals sciences and reliability engineering, the failure of individuals or units (I/Us) occurs due to independent causes failure. general, symmetry between dependent is essential nature problem at hand. this study, we considered accelerated competing risks model when lifetime I/Us was modeled using a generalized half-logistic distribution. The data were obtained with respect constant stress life tests (ALTs) type-II progressive censoring scheme. dependence structure formulated copula approach (symmetric Archimedean copula). parameters estimated maximum likelihood method; only two bivariate Pareto functions proposed. approximate confidence intervals constructed both asymptotic normality distribution MLEs bootstrap techniques. Additionally, an estimator system under normal level constructed. results from estimation methods tested by performing Monte Carlo simulation study. Finally, analysis sets levels performed for illustrative purposes.