Statistical Inference of Jointly Type-II Lifetime Samples under Weibull Competing Risks Models

Statistical Inference of a Competing Risks Model with Modified Weibull Distributions

Abstract Statistical inferences of the parameters included in a competing risks model are presented. It is assumed here that the causes of failures may occur at times that follow modified Weibull distributions. The case of Weibull distributions can be derived as special case of the problem studied in this paper. The maximum likelihood procedure is used to get the point estimations and asymptoti...

Statistical Inference for the Lomax Distribution under Progressively Type-II Censoring with Binomial Removal

This paper considers parameter estimations in Lomax distribution under progressive type-II censoring with random removals, assuming that the number of units removed at each failure time has a binomial distribution. The maximum likelihood estimators (MLEs) are derived using the expectation-maximization (EM) algorithm. The Bayes estimates of the parameters are obtained using both the squared erro...

exponentiated-Weibull distribution under type II censoring

This paper considers the three-parameter exponentiated Weibull family under type II censoring. It first graphically illustrates the shape property of the hazard function. Then, it proposes a simple algorithm for computing the maximum likelihood estimator and derives the Fisher information matrix. The latter one is represented through a single integral in terms of hazard function, hence it solve...

INFERENCE ON CENSORED SURVIVAL DATA UNDER COMPETING RISKS by

Statistical Inference Based on Progressively Type II Censored Data from Weibull Model

In this paper, we consider the problem of estimating the shape and scale parameters and predicting the unobserved removed data based on a progressive type II censored sample from the Weibull distribution. Maximum likelihood and Bayesian approaches are used to estimate the scale and shape parameters. The sampling-based method is used to draw Monte Carlo (MC) samples and it has been used to estim...