Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/236831 
Year of Publication: 
2021
Citation: 
[Journal:] Statistics in Transition New Series [ISSN:] 2450-0291 [Volume:] 22 [Issue:] 2 [Publisher:] Exeley [Place:] New York [Year:] 2021 [Pages:] 125-142
Publisher: 
Exeley, New York
Abstract: 
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.
Subjects: 
calibration
outliers
percentage relative efficiency (PRE)
stratified sampling
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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