Jackknife winsorized variance estimator under imputed data

• Authors: Fariha Sohil , Muhammad Umair Sohail , Javid Shabbir , Sat Gupta

Abstracts

EN

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.

Keywords

EN

adjusted imputation; jackknife variance estimators; linearized jackknife; missing values; winsorized variance

• Publisher: Główny Urząd Statystyczny
• Journal: Statistics in Transition new series
• Year: 2022
• Volume: 23
• Issue: 2
• Pages: 17-32

Dates

published

2022

Contributors

author

Fariha Sohil

• Department of Education, The Women University, Multan, Pakistan

author

Muhammad Umair Sohail

• Department of Statistics, University of Narowal, Narowal, Pakistan

• https://orcid.org/000000025440126X

author

Javid Shabbir

• Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan

• https://orcid.org/0000000200357072

author

Sat Gupta

• Department of Mathematics and Statistics, University of North Carolina, Greensboro, USA

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Identifiers

DOI

10.2478/stattrans-2022-0014

Biblioteka Nauki

2106879