VARIANCE ESTIMATORS USING NON-PARAMETRIC APPROACH UNDER DIFFERENT RANKED SET SAMPLING SCHEMES-Reference-Cited by-同舟云学术

VARIANCE ESTIMATORS USING NON-PARAMETRIC APPROACH UNDER DIFFERENT RANKED SET SAMPLING SCHEMES

Published:2023-09-30 Issue:3 Volume:23 Page:571-586
ISSN:2068-3049
Container-title:Journal of Science and Arts
language:en
Short-container-title:J. Sci. Arts

Author:

BEGUM NAEEMA¹,HANIF MUHAMMAD¹,SHAHZAD USMAN²,ALI NASIR¹

Affiliation:

1. Pir Mehr Ali Shah Arid Agriculture University Rawalpindi, Department of Statistics, 46300 Rawalpindi, Pakistan

2. Pir Mehr Ali Shah Arid Agriculture University Rawalpindi, Department of Statistics, 46300 Rawalpindi, Pakistan / International Islamic University, Department of Mathematics and Statistics, 44000 Islamabad, Pakistan.

Abstract

Estimation of variance is a commonly discussed topic under simple random sampling (SRS) scheme. The current article deals the issue of variance estimation utilizing supplementary information with the nonparametric approach under different ranked set sampling (RSS) schemes. We propose a class of nonparametric variance estimators utilizing kernel regression [1] with different bandwidths (Plug-in and Cross-validation), under RSS schemes. Simulation study is provided utilizing diverse data sets. The comparison of simulation results has been made between the members of the proposed class with respect to the unbiased variance estimator.

Publisher

Valahia University of Targoviste - Journal of Science and Arts

Subject

General Earth and Planetary Sciences,General Environmental Science

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