Estimation of Reliability Indices for Alpha Power Exponential Distribution Based on Progressively Censored Competing Risks Data

In reliability analysis and life testing studies, the experimenter is frequently interested in studying a specific risk factor presence of other factors. this paper, estimation unknown parameters, hazard functions alpha power exponential distribution considered based on progressively Type-II censored competing risks data. We assume that latent cause failures has independent distributions with different scale shape parameters. The maximum likelihood method to estimate model parameters as well rate functions. approximate two parametric bootstrap confidence intervals estimators are constructed. Moreover, Bayesian obtained squared error loss function using gamma priors. To get estimates highest posterior credible intervals, Markov Chain Monte Carlo procedure implemented. A comprehensive simulation experiment conducted compare performance proposed procedures. Finally, real dataset for relapse multiple myeloma transplant-related mortality analyzed.