1403/02/08
اکبر اصغر زاده

اکبر اصغر زاده

مرتبه علمی: استاد
ارکید:
تحصیلات: دکترای تخصصی
اسکاپوس:
دانشکده: دانشکده علوم ریاضی
نشانی:
تلفن: 011-54302476

مشخصات پژوهش

عنوان
Estimation and prediction for a progressively censored generalized inverted exponential distribution
نوع پژوهش
JournalPaper
کلیدواژه‌ها
Asymptotic confidence interval; Bayesian estimation; Equal-tail interval; HPD interval; Maximum likelihood estimation; MH algorithm; Prediction
سال
2016
مجله Statistical Methodology
شناسه DOI
پژوهشگران Sanku Dey ، Sukhdev Singh ، Yogesh Tripathi ، Akbar Asgharzadeh

چکیده

In this paper, we consider generalized inverted exponential distribution which is capable of modeling various shapes of failure rates and aging criteria. The purpose of this paper is two fold. Based on progressive type-II censored data, first we consider the problem of estimation of parameters under classical and Bayesian approaches. In this regard, we obtain maximum likelihood estimates, and Bayes estimates under squared error loss function. We also compute 95% asymptotic confidence interval and highest posterior density interval estimates under the respective approaches. Second, we consider the problem of prediction of future observations using maximum likelihood predictor, best unbiased predictor, conditional median predictor and Bayes predictor. The associated predictive interval estimates for the censored observations are computed as well. Finally, we analyze two real data sets and conduct a Monte Carlo simulation study to compare the performance of the various proposed estimators and predictors.