Record Details

Rescaling Bootstrap Variance Estimation of Level-0 Ranked Set Sampling under Finite Population Framework

KRISHI: Publication and Data Inventory Repository

View Archive Info
 
 
Field Value
 
Title Rescaling Bootstrap Variance Estimation of Level-0 Ranked Set Sampling under Finite Population Framework
Not Available
 
Creator Vinaykumar L.N.
Tauqueer Ahmad
Anil Rai
Ankur Biswas
 
Subject Ranks
Strata
Cluster
Level-0 Ranked Set Sampling
Rescaling bootstrap
Resampling
 
Description Not Available
McIntyre (1952) introduced Ranked Set Sampling (RSS) to advance upon Simple Random Sampling (SRS) for circumstances where any preliminary ranking of sampled units is possible for variable of interest using visual inspection or some other means without physically measuring the units. Further, the RSS was classified into three sampling protocols named as Level-0, Level-1 and Level-2 (Deshpande et al., 2006). The Level-0 sampling protocol of RSS is considered in this article. Estimating the variance of the Level-0 RSS estimator under the finite population framework was found to be cumbersome. In this article, two distinct rescaling bootstrap with replacement methods known as Strata-based rescaling bootstrap with-replacement (SRBWR) method and Cluster-based rescaling bootstrap with-replacement (CRBWR) method have been proposed to unbiasedly estimate the variance of Level-0 RSS estimator of finite population mean. Rescaling factors are obtained for both the proposed methods to estimate the variance of the Level-0 RSS estimator unbiasedly. The results of the simulation analysis, together with real data application support, proposed methods are capable of estimating the variance of the Level-0 RSS estimator almost unbiasedly. The developed SRBWR method performs better than the CRBWR method considering Relative stability (RS) and percentage Relative Bias (%RB) for various combinations of set size (m) and several cycles (r).
Not Available
 
Date 2023-07-05T09:18:29Z
2023-07-05T09:18:29Z
2021-12-31
 
Type Journal
 
Identifier Vinaykumar, L.N., Ahmad, T., Rai, A. and Biswas, A.* (2021). Rescaling Bootstrap Variance Estimation of Level-0 Ranked Set Sampling under Finite Population Framework. Journal of the Indian Society of Agricultural Statistics, 75(3), 203–211.
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/79676
 
Language English
 
Relation Not Available;
 
Publisher Journal of the Indian Society of Agricultural Statistics