使用依赖于辅助变量的复杂抽样设计来估计总体平均值

Q4 Mathematics

Statistics in Transition Pub Date : 2022-03-01 DOI:10.2478/stattrans-2022-0003

A. Chaudhuri, Sonakhya Samaddar

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引用次数: 2

摘要

摘要在调查有限总体时，无偏差估计总体的最简单策略是使用带替换的简单随机抽样（SRS）和基于它的扩展估计器。除无替换的SRS和使用扩展估计员外，任何其他策略都是复杂的策略。我们在这里检验（1）通过比较竞争策略的“竞争总体估计量”，是否可以从手头的复杂样本中无条件地估计效率增益；（2）通过模拟检验，竞争估计量的合适模型预期方差在大小上如何竞争。

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Estimating the population mean using a complex sampling design dependent on an auxiliary variable

Abstract In surveying finite populations, the simplest strategy to estimate a population total without bias is to employ Simple Random Sampling (SRS) with replacement (SRSWR) and the expansion estimator based on it. Anything other than that including SRS Without Replacement (SRSWOR) and usage of the expansion estimator is a complex strategy. We examine here (1) if from a complex sample at hand a gain in efficiency may be unbiasedly estimated comparing the “rival population total-estimators” for the competing strategies and (2) how suitable model-expected variances of rival estimators compete in magnitude as examined numerically through simulations.

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来源期刊

Statistics in Transition Decision Sciences-Statistics, Probability and Uncertainty

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

9 weeks

期刊介绍： Statistics in Transition (SiT) is an international journal published jointly by the Polish Statistical Association (PTS) and the Central Statistical Office of Poland (CSO/GUS), which sponsors this publication. Launched in 1993, it was issued twice a year until 2006; since then it appears - under a slightly changed title, Statistics in Transition new series - three times a year; and after 2013 as a regular quarterly journal." The journal provides a forum for exchange of ideas and experience amongst members of international community of statisticians, data producers and users, including researchers, teachers, policy makers and the general public. Its initially dominating focus on statistical issues pertinent to transition from centrally planned to a market-oriented economy has gradually been extended to embracing statistical problems related to development and modernization of the system of public (official) statistics, in general.