Maximum Likelihood Estimation for the New Kumaraswamy Pareto Distribution under Progressive Type II Censoring

Accepted March 2026

Abstract

Various distributions in current literature have been employed widely in modeling lifetime and reliability data such as the New Kumaraswamy Pareto (NKP) distribution, which belongs to the New Generalised Family of distributions. Although the NKP has been studied under complete and bootstrap sampling schemes, little is known of its behaviour with censored observations, specifically progressive Type-II censoring. In this paper, we obtain the Maximum Likelihood Estimates (MLEs) of parameters of NKP under progressive Type-II censoring. A Monte Carlo simulation evaluates estimator performance across varying sample sizes (n), number of observed failures (m), and three censoring schemes. Bias and mean squared error (MSE) are used to assess accuracy and precision.