Bayesian reconstruction of the missing failure times in exponential distribution

Abstract

In this paper, we consider the situations in which a middle part of the sample is lost or removed from the experiment. The left-censored sample and Type-II right-censored sample are special cases of this scheme. Point and interval reconstructors for lost failure times are obtained, while the underlying distribution is exponential. To illustrate the performance of the proposed procedures, two numerical examples based on the real data sets are presented. In the case of two-parameter, a simulation study has been done and also the sensitivity of the results to deviations from the true distribution is investigated.

A New Algorithm to Impute the Missing Values in the Multivariate Case

“…Then, some point and interval reconstruction are computed for the missing order statistics in the exponential distribution using the classic approach Razmkhah et al (2010). This study was examined using the Bayes approach Khatib et al (2013). A novel method based on the projection theorem, is proposed by Almasi et al (2017) to reconstruct the missing order statistics.…”

Reconstruction of Past Failure Times for Left Type-II Censored Data from Weibull Model

“…Asgharzadeh et al (2012) discussed reconstructors of times to failure of units censored in a leftcensored sample from the proportional reversed hazard rate models. Khatib et al (2013) have considered the Bayesian reconstruction of the missing failure times in exponential distribution. Asgharzadeh et al (2014) studied the estimation and reconstruction problems for the two-parameter Pareto distribution based on the left censored data.…”