文章基本信息

标题：Inference for exponentiated general class of distributions based on record values
本地全文：下载
作者：Samah N. Sindi ; Gannat R. Al-Dayian ; Saman Hanif Shahbaz 等
期刊名称：Pakistan Journal of Statistics and Operation Research
印刷版ISSN：2220-5810
出版年度：2017
卷号：13
期号：3
页码：575-587
DOI：10.18187/pjsor.v13i3.2069
语种：English
出版社：College of Statistical and Actuarial Sciences
摘要：The main objective of this paper is to suggest and study a new exponentiated general class (EGC) of distributions. Maximum likelihood, Bayesian and empirical Bayesian estimators of the parameter of the EGC of distributions based on lower record values are obtained. Furthermore, Bayesian prediction of future records is considered. Based on lower record values, the exponentiated Weibull distribution, its special cases of distributions and exponentiated Gompertz distribution are applied to the EGC of distributions.
其他摘要：The main objective of this paper is to suggest and study a new exponentiated general class (EGC) of distributions. Maximum likelihood, Bayesian and empirical Bayesian estimators of the parameter of the EGC of distributions based on lower record values are obtained. Furthermore, Bayesian prediction of future records is considered. Based on lower record values, the exponentiated Weibull distribution, its special cases of distributions and exponentiated Gompertz distribution are applied to the EGC of distributions.
关键词：Lower record values; maximum likelihood estimation; Bayesian estimation; empirical Bayesian estimation; Bayesian prediction