Jackknife winsorized variance estimator under imputed data

Q4 Mathematics

Statistics in Transition Pub Date : 2022-06-01 DOI:10.2478/stattrans-2022-0014

Fariha Sohil, M. U. Sohail, J. Shabbir, Sat Gupta

引用次数: 0

Abstract

Abstract In the present study, we consider the problem of missing and extreme values for the estimation of population variance. The presence of extreme values either in the study variable, or the auxiliary variable, or in both of them, can adversely affect the performance of the estimation procedure. We consider three different situations for the presence of extreme values and also consider jackknife variance estimators for the population variance by handling these extreme values under stratified random sampling. Bootstrap technique ABB is carried out to understand the relative relationship more precisely.

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估算数据下的Jackknife winsorized方差估计

摘要在本研究中，我们考虑了群体方差估计的缺失值和极值问题。研究变量、辅助变量或二者中存在极值，可能会对估计程序的性能产生不利影响。我们考虑了极值存在的三种不同情况，并通过在分层随机抽样下处理这些极值，考虑了总体方差的jackknife方差估计量。ABB的Bootstrap技术是为了更准确地理解相对关系。

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

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.