Exact likelihood inference for two exponential populations based on a joint generalized Type-I hybrid censored sample. Issue 7 (2nd May 2016)

• Record Type: Journal Article
• Authors: Su, Feng; Zhu, Xiaojun
• Is Part Of: Journal of statistical computation and simulation. Volume 86:Issue 7(2016)
• Page Start: 1342
• Page End: 1362
• Publication Date: 2016-05-02
• Subjects: conditional MLEs -- exact confidence interval -- exponential distribution -- joint generalized Type-I hybrid censoring -- likelihood inference -- MSEs; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2015.1062483
• Languages: English
• ISSNs: 0094-9655

Abstract

Abstract : Following the work of Chen and Bhattacharyya [Exact confidence bounds for an exponential parameter under hybrid censoring. Comm Statist Theory Methods. 1988;17:1857–1870], several results have been developed regarding the exact likelihood inference of exponential parameters based on different forms of censored samples. In this paper, the conditional maximum likelihood estimators (MLEs) of two exponential mean parameters are derived under joint generalized Type-I hybrid censoring on the two samples. The moment generating functions (MGFs) and the exact densities of the conditional MLEs are obtained, using which exact confidence intervals are then developed for the model parameters. We also derive the means, variances, and mean squared errors of these estimates. An efficient computational method is developed based on the joint MGF. Finally, an example is presented to illustrate the methods of inference developed here.