فهرست نشریات علمی دسترسی آزاد ایران

This paper investigates the reliability and parametric inference for the inverse power Maxwell distribution under progressive Type-II censored sample. Under the frequentist approach, the maximum likelihood estimate, least square, and weighted least square methods are considered for estimating the model parameters and any parametric function involved in this model. Approximate confidence intervals for parameters and any of their functions are created via a variance-covariance matrix. Bayes estimates are obtained using Lindley's approximation and Markov chain Monte Carlo (MCMC) technique under squared error loss function. Additionally, the highest posterior density (HPD) credible intervals are constructed using MCMC approximation techniques. A comprehensive Monte Carlo simulation study is conducted to assess the efficiency of the proposed methodologies. Furthermore, three optimality criteria are presented to choose the most suitable progressive scheme from various sampling plans. The practical utility of the proposed methods is demonstrated using two real-world datasets: the failure times of mechanical components and the strength of glass fiber.