Bayes Prediction on Optimum SS-PALT in Generalized Inverted Exponential Distribution: A Two-Sample Approach

Abstract

The generalized Inverted Exponential distribution is considered for the study on Optimum Step Stress Partially Accelerated Life Test (SS-PALT) based on different censoring patterns. The first-failure progressive censoring (FFPC) scheme and their special cases are used in the present study. A two-sample Bayes Prediction Bound Length (TS-BPBL) under SS-PALT on FFPC have been obtained and studied their properties by using different special cases of FFPC. Based on simulated and real data set, the properties of the ML estimates and the approximate confidence length under the normal approximation, also have been studied.