Artikel

Developing calibration estimators for population mean using robust measures of dispersion under stratified random sampling

In this paper, two modified, design-based calibration ratio-type estimators are presented. The suggested estimators were developed under stratified random sampling using information on an auxiliary variable in the form of robust statistical measures, including Gini's mean difference, Downton's method and probability weighted moments. The properties (biases and MSEs) of the proposed estimators are studied up to the terms of firstorder approximation by means of Taylor's Series approximation. The theoretical results were supported by a simulation study conducted on four bivariate populations and generated using normal, chi-square, exponential and gamma populations. The results of the study indicate that the proposed calibration scheme is more precise than any of the others considered in this paper.

Sprache
Englisch

Erschienen in
Journal: Statistics in Transition New Series ; ISSN: 2450-0291 ; Volume: 22 ; Year: 2021 ; Issue: 2 ; Pages: 125-142 ; New York: Exeley

Thema
calibration
outliers
percentage relative efficiency (PRE)
stratified sampling

Ereignis
Geistige Schöpfung
(wer)
Audu, Ahmed
Singh, Rajesh
Khare, Supriya
Ereignis
Veröffentlichung
(wer)
Exeley
(wo)
New York
(wann)
2021

DOI
doi:10.21307/stattrans-2021-019
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

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Objekttyp

  • Artikel

Beteiligte

  • Audu, Ahmed
  • Singh, Rajesh
  • Khare, Supriya
  • Exeley

Entstanden

  • 2021

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