مشخصات پژوهش

عنوان	Optimal Sample Size in Type-II Progressive Censoring Using a Bayesian Prediction Approach
نوع پژوهش	مقاله چاپ شده
کلیدواژه‌ها	optimization problem, general entropy loss function, Bayes risk function, prediction.
چکیده	This paper considers the progressively Type-II censoring and determines the optimal sample size using a Bayesian prediction approach. To this end, two criteria, namely the Bayes risk function of the point predictor for a future progressively censored order statistic and the designing cost of the experiment are considered. In the Bayesian prediction, the general entropy loss function is applied. We find the optimal sample size such that the Bayes risk function and the cost of the experiment do not exceed two pre-fixed values. To show the usefulness of the results, some numerical computations are presented.
پژوهشگران	سیدمحمدتقی کامل میرمصطفائی (نفر دوم)، الهام بصیری (نفر اول)