1403/02/06
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
Point and interval estimation for the logistic distribution based on record data
نوع پژوهش
JournalPaper
کلیدواژه‌ها
Logistic distribution; record data;maximum likelihood estimator; Bayes estimator; Gibbs sampling.
سال
2016
مجله SORT-Statistics and Operations Research Transactions
شناسه DOI
پژوهشگران Reza Valiollahi ، Mosa Abdi ، Akbar Asgharzadeh

چکیده

In this paper, based on record data from the two-parameter logistic distribution, the maximum likelihood and Bayes estimators for the two unknown parameters are derived. The maximum like- lihood estimators and Bayes estimators can not be obtained in explicit forms.We present a simple method of deriving explicit maximum likelihood estimators by approximating the likelihood func- tion. Also, an approximation based on the Gibbs sampling procedure is used to obtain the Bayes estimators. Asymptotic confidence intervals, bootstrap confidence intervals and credible intervals are also proposed. Monte Carlo simulations are performed to compare the performances of the different proposed methods. Finally, one real data set has been analysed for illustrative purposes.