双重抽样下总体均值的泊松回归比估计，并应用于Covid-19

IF 1.4 3区社会学 Q3 DEMOGRAPHY

Mathematical Population Studies Pub Date : 2022-05-03 DOI:10.1080/08898480.2022.2051988

H. Koç, Caner Tanış, T. Zaman

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引用次数: 5

摘要

用泊松回归处理计数数据。将总体均值的泊松回归比估计从单采样推广到双采样。这可以通过提供辅助变量的总体平均值来实现。所提出的估计量的均方误差表示到一阶。理论和数值结果表明，所提出的双采样泊松回归比估计比双采样和单采样估计具有更小的均方误差。对于新冠肺炎，该方法的最小均方误差分别为每天0.095例和67.8例，而双比方法的最小均方误差分别为每天0.112例和84.8例。

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Poisson regression-ratio estimators of the population mean under double sampling, with application to Covid-19

ABSTRACT Poisson regression is used to deal with count data. The Poisson regression ratio estimator of the population mean is extended from single to double sampling. This is made possible by the provision of the population mean of an auxiliary variable. The mean square errors of the proposed estimators are expressed up to the first order. Theoretical and numerical results demonstrate that the proposed double-sampling Poisson-regression ratio estimator has a lower mean square error than the double-ratio and the single-sampling estimator. For Covid-19, the minimum mean square errors yielded by the proposed estimator of the total number of cases are 0.095 cases per day and 67.8 cases, compared with 0.112 cases per day and 84.8 cases with the double-ratio estimator.

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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.