Statistical Inference of Accelerated Ishita Model Based on Type-I Generalized Hybrid Censoring Data with Applications (European Journal of Pure and Applied Mathematics, 2025)
In this paper, we adopt the Ishita lifetime distribution to analyze biomedical science and engineering lifetime data under an accelerated life test (ALT) model. This data is exposed concerning the mechanism of a type-I generalized hybrid censoring scheme under a partially step-stress ALT model. The model parameters and the parameters of life (survival and hazard rate function) are estimated using maximum likelihood and Bayesian estimation. Also, the interval estimators are formulated with respect to the normal distribution of the maximum likelihood estimate, two parametric bootstrap confidence techniques, and Bayesian credible intervals. Two real data sets are analyzed to illustrate the proposed methods. Monte Carlo simulation is used to compare various methods.
Keywords: Bayesian estimation; Bootstrap confidence interval; Classical estimation; Generalized hybrid censoring scheme; Ishita distribtution; MCMC.