Title : Statistical inference based on record data from pareto model ( Statistical inference based on record data from Pareto model )
Authors: محمد الرقاب , Jafar Ahmadi , Mahdi Doostparast ,
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Abstract
In this paper, based on record values from the two-parameter Pareto distribution, maximum likelihood and Bayes estimators for the two unknown parameters are obtained. The Bayes estimates are obtained based on the squared error loss (SEL) and linear-exponential (LINEX) loss functions. The admissibility of some estimators are discussed. The problem of predicting the future record values, either point or interval, from the Pareto distribution, based on the past record values observed, is considered from a Bayesian approach. Also, the maximum likelihood prediction of the future records as well as other classical methods have been used for obtaining prediction intervals for the future records. Numerical computations are given for an empirical comparison purposes.
Keywords
, Admissibility; Bayes estimation; Bayes prediction; Squared error loss; Linear, exponential loss; Maximum likelihood prediction
@article{paperid:203667,
author = {محمد الرقاب and Ahmadi, Jafar and Doostparast, Mahdi},
title = {Statistical inference based on record data from pareto model},
journal = {Statistics},
year = {2007},
volume = {41},
number = {2},
month = {April},
issn = {0233-1888},
pages = {105--118},
numpages = {13},
keywords = {Admissibility; Bayes estimation; Bayes
prediction; Squared error loss; Linear-exponential loss; Maximum
likelihood prediction},
}
%0 Journal Article
%T Statistical inference based on record data from pareto model
%A محمد الرقاب
%A Ahmadi, Jafar
%A Doostparast, Mahdi
%J Statistics
%@ 0233-1888
%D 2007
