Maximum Likelihood Estimation for Generalized Pareto Distribution under Progressive Censoring with Binomial Removals
نویسنده
چکیده
The paper deals with the estimation problem for the generalized Pareto distribution based on progressive type-II censoring with random removals. The number of components removed at each failure time is assumed to follow a binomial distribution. Maximum likelihood estimators and the asymptotic variance-covariance matrix of the estimates are obtained. Finally, a numerical example is given to illustrate the obtained results.
منابع مشابه
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...
متن کاملReliability estimation in Pareto-I distribution based on progressively type II censored sample with binomial removals
108 Reliability estimation in Pareto-I distribution based on progressively type II censored sample with binomial removals Ilhan USTA 1, *, Hanefi Gezer 2 1Doctor of Philosophy, Associate Professor, Department of Statistics, Faculty of Science, Anadolu University, Eskisehir, Turkey 2Master of Statistics, Faculty of Science, Anadolu University, Eskisehir, Turkey Abstract: In this study, we deal w...
متن کاملInference for the Type-II Generalized Logistic Distribution with Progressive Hybrid Censoring
This article presents the analysis of the Type-II hybrid progressively censored data when the lifetime distributions of the items follow Type-II generalized logistic distribution. Maximum likelihood estimators (MLEs) are investigated for estimating the location and scale parameters. It is observed that the MLEs can not be obtained in explicit forms. We provide the approximate maximum likelihood...
متن کاملEstimation for Burr-X model based on progressively censored with random removals: Bayesian and non-Bayesian Approaches
Abstract: This paper considers the estimation problem for the Burr type-X, when the lifetimes are collected under Type-II progressive censoring with random removals, where the number of units removed at each failure time follows a binomial distribution. We use the methods of maximum likelihood as well as the Bayes procedure to derive both point and interval estimators of the parameters. The exp...
متن کاملEstimation in Simple Step-Stress Model for the Marshall-Olkin Generalized Exponential Distribution under Type-I Censoring
This paper considers the simple step-stress model from the Marshall-Olkin generalized exponential distribution when there is time constraint on the duration of the experiment. The maximum likelihood equations for estimating the parameters assuming a cumulative exposure model with lifetimes as the distributed Marshall Olkin generalized exponential are derived. The likelihood equations do not lea...
متن کامل