Inferences for Joint Hybrid Progressive Censored Exponential Lifetimes under Competing Risk Model

Abstract

The aim of this paper is devoted to the problem of comparative life tests under joint censoring samples from an exponential distribution with competing risks model. This problem is considered under the consideration that only two causes of failure are occurring and the units come from two production lines such that the exponential failure time of units is censored under a hybrid progressive Type-I censoring scheme. Maximum likelihood estimation and different Bayes methods of estimation are discussed. The asymptotic confidence intervals as well as the Bayes credible intervals are established. A real data set representing time to failure on two groups of strain male mice receiving radiation is analyzed for illustrative purposes. All theoretical results are assessed and compared through the Monte Carlo study.

Statistical Inferences of Burr XII Lifetime Models under Joint Type-1 Competing Risks Samples

“…Recently, the joint censoring scheme is more widely used in a comparative life testing specially for products coming from different lines of production. e problem of comparative life testes under different causes of failure has been discussed recently under the joint censoring scheme of competing risks exponential lifetime model by Almarashi et al [15]. In this paper, we adopted this problem when units or individual is distributed with Burr XII distributions.…”

“…(7) e values of each ME, MSEs, MILs, and PCs are computed and reported in Tables 5-8. ALGORITHM 2: General steps used to generate Type-I joint competing risk samples and the corresponding estimate (see Almarashi et al [15]).…”

“…And, this problem is handled recently by Al-Matrafi and Abd-Elmougod [11], Momenkhan and Abd-Elmougod [12], Mondal and Kundu [13], and Mondal andKundu [14]. e problem of statistical inference under jointly censoring schemes with the competing risks model is recently discussed by Almarashi et al [15].…”

Estimation for Akshaya Failure Model with Competing Risks under Progressive Censoring Scheme with Analyzing of Thymic Lymphoma of Mice Application

“…( 9) For the given study, the parameter p of the binomial distribution is to be considered same in the whole experiment. (10) We assume that the random variable T ji follows Akshaya distributions with unknown parameter θ j , Discussed the analysis of progressively censored competing risks data [36]. Pareek et al (2009) Explored the application of Weibull distribution to compting risk model under progressive censoring scheme [37].…”

“…Jiang [9] considered the Poisson shock model using masked system life data and obtained ML and Bayes estimator of parameter and survival function of each component with influence of the making level. Almarashi et al [10] considered the two causes of failure, where the lifetime units come from the exponential failure distribution. e units is censored under a hybrid progressive type-I censoring scheme.…”