Comparing Interval Estimators for Reliability in a Dependent Set-up

Abstract

In this paper some procedures for building confidence intervals for the reliability in stress-strength models are discussed and empirically compared. The particular case of a bivariate normal setup is considered. The confidence intervals suggested are obtained employing approximations or asymptotic properties of maximum likelihood estimators. The coverage and the precision of these intervals are empirically checked through a simulation study. An application to real paired data is also provided. Keywords—approximate estimators, asymptotic theory, confidence interval, Monte Carlo simulations, stress-strength, variance estimation.