On use of adaptive cluster sampling for variance estimation

© 2025 Informa UK Limited, trading as Taylor & Francis Group.

Détails bibliographiques
Publié dans:Journal of applied statistics. - 1991. - 52(2025), 12 vom: 03., Seite 2291-2305
Auteur principal: Alam, Shameem (Auteur)
Autres auteurs: Shabbir, Javid, Nadeem, Malaika
Format: Article en ligne
Langue:English
Publié: 2025
Accès à la collection:Journal of applied statistics
Sujets:Journal Article Adaptive cluster sampling auxiliary information bias mean square error
Description
Résumé:© 2025 Informa UK Limited, trading as Taylor & Francis Group.
Adaptive cluster sampling is particularly helpful whenever the target population is unique, dispersed unevenly, concealed or difficult to find. In the current investigation, under an adaptive cluster sampling approach, we propose a ratio-product-logarithmic type estimator employing a single auxiliary variable for the estimation of finite population variance. The bias and mean square error of the proposed estimator are developed by using simulation as well as real data sets. The study results show that for estimating the finite population variance, the proposed estimator outperforms the competing estimators
Description:Date Revised 10.09.2025
published: Electronic-eCollection
Citation Status In-Process
ISSN:0266-4763
DOI:10.1080/02664763.2025.2460072