Maximum likelihood estimation of the parameters of the inverse Gaussian distribution using maximum rank set sampling with unequal samples

IF 1.4 3区社会学 Q3 DEMOGRAPHY

Mathematical Population Studies Pub Date : 2021-12-27 DOI:10.1080/08898480.2021.1996822

Shuo Wang, Wangxue Chen, Meng Chen, Ya Zhou

引用次数: 7

Abstract

ABSTRACT Maximum ranked set sampling with unequal samples is a sampling procedure used to reduce the error of ranking of observations and increase the efficiency of statistical inference. It is used for maximum likelihood estimation of the location and shape parameters of the inverse Gaussian distribution. Its asymptotic efficiency is at least 1.4 times higher than those of estimators based on simple random sampling. It is useful in reliability studies and in Bayesian statistics involving the inverse Gaussian distribution.

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利用不等样本最大秩集采样的逆高斯分布参数的最大似然估计

不等样本最大排序集抽样是一种用于减少观测值排序误差和提高统计推断效率的抽样方法。它用于高斯反分布的位置和形状参数的极大似然估计。它的渐近效率比基于简单随机抽样的估计器至少高1.4倍。它在可靠性研究和涉及逆高斯分布的贝叶斯统计中很有用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mathematical Population Studies 数学-数学跨学科应用

CiteScore

3.20

自引率

11.10%

发文量

审稿时长

>12 weeks

期刊介绍： Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions. The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.