On confidence bounds for one-parameter exponential families

被引：0

作者：

Alizadeh, M. ^{[1
]}

Nadarajah, S. ^{[2
]}

Doostparast, M. ^{[3
]}

Parchami, A. ^{[1
]}

Mashinchi, M. ^{[1
]}

机构：

[1] Shahid Bahonar Univ Kerman, Dept Stat, Kerman, Iran

[2] Univ Manchester, Sch Math, Manchester, Lancs, England

[3] Ferdowsi Univ Mashhad, Sch Math Sci, Dept Stat, Mashhad, Iran

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2017年 / 46卷 / 02期

关键词：

Coverage length; Coverage probability; HPD credible interval; One-parameter exponential family; Pivotal quantity method; Relative surprise credible interval; Unbiased confidence interval; BAYESIAN-INFERENCE; WEIBULL FAMILY; INTERVALS; PREDICTION;

D O I：

10.1080/03610918.2015.1006776

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

There exist various methods for providing confidence intervals for unknown parameters of interest on the basis of a random sample. Generally, the bounds are derived from a system of non-linear equations. In this article, we present a general solution to obtain an unbiased confidence interval with confidence coefficient 1 - in one-parameter exponential families. Also we discuss two Bayesian credible intervals, the highest posterior density (HPD) and relative surprise (RS) credible intervals. Standard criteria like the coverage length and coverage probability are used to assess the performance of the HPD and RS credible intervals. Simulation studies and real data applications are presented for illustrative purposes.

引用

页码：1569 / 1582

页数：14

共 39 条

[1] Estimation and prediction in a two-parameter exponential distribution based on k-record values under LINEX loss function [J].