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Akbar Asgharzadeh

Akbar Asgharzadeh

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId:
Faculty: Faculty of Mathematical Sciences
Address: Department of Statistics University of Mazandaran Babolsar, IRAN
Phone: 011-54302476

Research

Title
Bayesian Inference and Prediction for Normal Distribution Based on Records
Type
JournalPaper
Keywords
Bayesian prediction; Best linear unbiased estimators; Maximum likelihood estimators; Record data.
Year
2018
Journal STATISTICA
DOI
Researchers Akbar Asgharzadeh ، Reza Valiollahi ، Adeleh Fallah ، Saralees Nadarajah

Abstract

Based on record data, the estimation and prediction problems for normal distribution have been investigated by several authors in the frequentist set up. However, these problems have not been discussed in the literature in the Bayesian context. The aim of this paper is to consider a Bayesian analysis in the context of record data from a normal distribution. We obtain Bayes estimators based on squared error and linear-exponential (Linex) loss functions. It is observed that the Bayes estimators can not be obtained in closed forms. We propose using an importance sampling method to obtain Bayes estimators. Further, the importance sampling method is also used to compute Bayesian predictors of future records. Finally, a real data analysis is presented for illustrative purposes and Monte Carlo simulations are performed to compare the performances of the proposed methods. It is shown that Bayes estimators and predictors are superior than frequentist estimators and predictors.