Hazard Estimation under Generalized Censoring
نویسندگان
چکیده
This paper focuses on the problem of the estimation of the cumulative hazard function of a distribution on a general complete separable metric space when the data points are subject to censoring by an arbitrary adapted random set. A problem involving observability of the estimator proposed in [8] and [9] is resolved and a functional central limit theorem is proven for the revised estimator. Several examples and applications are discussed, and the validity of bootstrap methods is established in each case.
منابع مشابه
Estimation 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 کاملE-Bayesian Estimations of Reliability and Hazard Rate based on Generalized Inverted Exponential Distribution and Type II Censoring
Introduction This paper is concerned with using the Maximum Likelihood, Bayes and a new method, E-Bayesian, estimations for computing estimates for the unknown parameter, reliability and hazard rate functions of the Generalized Inverted Exponential distribution. The estimates are derived based on a conjugate prior for the unknown parameter. E-Bayesian estimations are obtained based on th...
متن کاملBayesian Analysis for the Generalized Rayleigh Distribution
In this paper, the estimation problem of generalized Rayleigh distribution is considered. The parameters are estimated using likelihood based inferential procedure: classical as well as Bayesian. We have computed MLEs and Bayes estimates under gamma priors along with their asymptotic confidence, bootstrap and HPD intervals. The Bayesian estimates of the parameters of generalized Rayleigh distri...
متن کاملSieve estimation in a Markov illness-death process under dual censoring.
Semiparametric methods are well established for the analysis of a progressive Markov illness-death process observed up to a noninformative right censoring time. However, often the intermediate and terminal events are censored in different ways, leading to a dual censoring scheme. In such settings, unbiased estimation of the cumulative transition intensity functions cannot be achieved without so...
متن کاملMaximum Likelihood Estimation for Generalized Pareto Distribution under Progressive Censoring with Binomial Removals
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 illu...
متن کامل