单迭代Farlie–Gumbel–Morgenstern双变量分布的有序统计信息测度及其伴随

IF 1.4 3区社会学 Q3 DEMOGRAPHY Mathematical Population Studies Pub Date : 2020-07-20 DOI:10.1080/08898480.2020.1767926

H. M. Barakat, E. Nigm, I. A. Husseiny

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引用次数: 11

摘要

摘要在迭代Farlie–Gumbel–Morgenstern双变量分布的形状参数向量的情况下，获得了与阶统计量相关的Fisher信息矩阵及其用于对双变量随机样本进行排序的伴随矩阵。它们包含从迭代的Farlie–Gumbel–Morgenstern双变量分布中提取的单删失或多重删失双变量样本所传达的信息。Fisher信息是为伴随阶统计量的指数分布的平均值计算的。基于迭代的Farlie–Gumbel–Morgenstern二元分布，导出了阶统计量中的Shannon熵及其伴随项。

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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Measures of information in order statistics and their concomitants for the single iterated Farlie–Gumbel–Morgenstern bivariate distribution

ABSTRACT The Fisher information matrix related to an order statistic and its concomitant used to order a bivariate random sample are obtained in the case of the shape-parameter vector of an iterated Farlie–Gumbel–Morgenstern bivariate distribution. They contain information conveyed by singly or multiply censored bivariate samples drawn from an iterated Farlie–Gumbel–Morgenstern bivariate distribution. Fisher information is computed for the mean of the exponential distribution in the concomitant of an order statistic. Shannon entropy in the order statistics and their concomitants based on the iterated Farlie–Gumbel–Morgenstern bivariate distribution are derived.

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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.