مشخصات پژوهش

عنوان	Non-Bayesian two-Sample Prediction for Progressively Type-II Censored Weibull Lifetimes
نوع پژوهش	مقاله ارائه‌شده
کلیدواژه‌ها	‎Approximate maximum likelihood prediction‎, ‎EM algorithm; Maximum likelihood prediction‎, ‎Mean square prediction error‎, ‎Progressive Type-II right censoring scheme‎, ‎Two-sample prediction.
چکیده	‎Prediction on the basis of censored data has an important role in many fields‎. ‎This paper develops a non-Bayesian two-sample prediction based on a progressive Type-II right censoring scheme‎. ‎We obtain the maximum likelihood (ML) prediction in the Weibull distribution‎. ‎The Weibull distribution is considered to obtain the ML predictor (MLP) and the predictive ML estimators of the s-th order statistic in a future random sample Y_s drawn independently from the parent population‎, ‎for an arbitrary progressive censoring scheme‎. ‎To reach this aim‎, ‎we present two ML prediction methods namely the EM algorithm and the approximate ML prediction‎. ‎We compare the performances of the different methods of ML prediction by Monte Carlo simulation with respect to biases and mean square prediction errors (MSPEs) of the MLPs of Y_s.
پژوهشگران	سمیه غفوری (نفر اول)