Open AccessStatistical inferences based on an adaptive progressive type-II censoring from exponentiated exponential distribution
Author(s) -
Saieed F. Ateya,
Heba S. Mohammed
Publication year - 2017
Publication title -
journal of the egyptian mathematical society
Language(s) - English
Resource type - Journals
eISSN - 2090-9128
pISSN - 1110-256X
DOI - 10.1016/j.joems.2017.06.001
Subject(s) - censoring (clinical trials) , mathematics , statistics , exponential distribution , bayes' theorem , exponential function , interval estimation , confidence interval , point estimation , bayesian probability , mathematical analysis
In this paper, the estimation problem (point and interval) is studied under the exponentiated exponential (EE) distribution based on an adaptive progressive type-II censoring scheme. In point estimation, the maximum likelihood estimates (MLEâ²s) and Bayes estimates (BEâ²s), based on squared error (SE) and linear exponential (LINEX) loss functions, are computed. Also, the approximate confidence intervals for the parameters of EE distribution are obtained. A comparison study is made between the BEâ²s and MLEâ²s using the estimated risks (ERâ²s) criterion. Finally, point and interval estimations of all parameters are studied based on a generated adaptive type-II progressive censoring sample from a real data set as illustrative example. Keywords: Exponentiated exponential distribution, Adaptive progressive type-II censoring, Markov Chain Monte Carlo method, MSC: 62F10, 62F15, 62N01, 62N0