Exact Inference for the Two-Parameter Exponential Distribution Under Type-II Hybrid Censoring
نویسندگان
چکیده
Epstein [9] introduced the Type-I hybrid censoring scheme as a mixture of Type-I and Type-II censoring schemes. Childs et al. [5] introduced the Type-II hybrid censoring scheme as an alternative to Type-I hybrid censoring scheme, and provided the exact distribution of the maximum likelihood estimator of the mean of a one parameter exponential distribution based on Type-II hybrid censored samples. The associated confidence interval also has been provided. The main aim of this paper is to consider a two-parameter exponential distribution, and to derive the exact distribution of the maximum likelihood estimators of the unknown parameters based on Type-II hybrid censored samples. The marginal distributions and the exact confidence intervals are also provided. The results can be used to derive the exact distribution of the maximum likelihood estimator of the percentile point, and to construct the associated confidence interval. Different methods are compared using extensive simulations and one data analysis has been performed for illustrative purposes.
منابع مشابه
Exact hypothesis testing and confidence interval for mean of the exponential distribution under Type-I progressive hybrid censoring
Censored samples are discussed in experiments of life-testing; i.e. whenever the experimenter does not observe the failure times of all units placed on a life test. In recent years, inference based on censored sampling is considered, so that about the parameters of various distributions such as normal, exponential, gamma, Rayleigh, Weibull, log normal, inverse Gaussian, ...
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 کاملStatistical 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 کاملAn EM Algorithm for Estimating the Parameters of the Generalized Exponential Distribution under Unified Hybrid Censored Data
The unified hybrid censoring is a mixture of generalized Type-I and Type-II hybrid censoring schemes. This article presents the statistical inferences on Generalized Exponential Distribution parameters when the data are obtained from the unified hybrid censoring scheme. It is observed that the maximum likelihood estimators can not be derived in closed form. The EM algorithm for computing the ma...
متن کاملClassical and Bayesian Inference in Two Parameter Exponential Distribution with Randomly Censored Data
Abstract. This paper deals with the classical and Bayesian estimation for two parameter exponential distribution having scale and location parameters with randomly censored data. The censoring time is also assumed to follow a two parameter exponential distribution with different scale but same location parameter. The main stress is on the location parameter in this paper. This parameter has not...
متن کامل