Evaluating the lifetime performance index of the generalised half-logistic population in the generalised Type I hybrid censoring scheme

Abstract

Researchers can use many statistical tools to fit data, either simple or complex, based on the likelihood. However, more parameters usually provide a smooth resolution, due to the order of likelihood increases, however, the main issue is to use special tools to estimate parameters. For example, we are used the process capability indices (CL) for measuring the performance of a process with, lower specification limit L). The article adopts a method of CL when the unit’s lifetime has two parameters generalised half-logistic lifetime population. The real-world dataset is collected with respected to Type-I generalised hybrid censoring scheme. The scale parameter is specified under data transformation technology. The Bayes and maximum likelihood estimators are formulated using the conjugate form of the prior and examined using the squared error loss procedure. The developed estimators construct credible and confidence intervals for CL. Real world examples in this article illustrate the pattern of the estimate value of confidence interval for the parameter CL and the interval estimations of CL are assessed by a Monte Carlo simulation studies.

Keywords

• Generalised half-logistic distribution
• Generalised Type-I hybrid censoring scheme
• Process capability indices
• Confidence interval
• Credible interval