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GWR-assisted integrated estimator of finite population total under two-phase sampling: a model-assisted approach

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Title GWR-assisted integrated estimator of finite population total under two-phase sampling: a model-assisted approach
Not Available
 
Creator Nobin Chandra Paul
Anil Rai
Tauqueer Ahmad
Ankur Biswas
Prachi Misra Sahoo
 
Subject Data integration
geographically weighted regression
model-assisted approach
spatial non-stationarity
two-phase regression
 
Description In survey sampling, auxiliary information is used to precisely estimate the finite population parameters. There are several approaches available in the literature that provide a practical method for incorporating auxiliary information during the estimation stage. In order to effectively utilize the auxiliary information, a geographically weighted regression (GWR) model-assisted integrated estimator of finite population total under a two-phase sampling design has been proposed in this article. Spatial simulation studies have been conducted to empirically assess the statistical properties of the proposed estimator. In the presence of spatial non-stationarity, empirical findings reveal that the proposed estimator outperforms all existing estimators such as two-phase HT, ratio, and regression estimators, demonstrating the importance of spatial information in survey sampling.
In survey sampling, auxiliary information is used to precisely estimate the finite population parameters. There are several approaches available in the literature that provide a practical method for incorporating auxiliary information during the estimation stage. In order to effectively utilize the auxiliary information, a geographically weighted regression (GWR) model-assisted integrated estimator of finite population total under a two-phase sampling design has been proposed in this article. Spatial simulation studies have been conducted to empirically assess the statistical properties of the proposed estimator. In the presence of spatial non-stationarity, empirical findings reveal that the proposed estimator outperforms all existing estimators such as two-phase HT, ratio, and regression estimators, demonstrating the importance of spatial information in survey sampling.
Not Available
 
Date 2023-11-22T12:23:52Z
2023-11-22T12:23:52Z
2023-11-14
 
Type Research Paper
 
Identifier Paul, N.C., Rai, A., Ahmad, T., Biswas, A., and Sahoo, P.M. (2023). GWR-assisted integrated estimator of finite population total under two-phase sampling: a model-assisted approach. Journal of Applied Statistics. https://doi.org/10.1080/02664763.2023.2280879
0266-4763
http://krishi.icar.gov.in/jspui/handle/123456789/80916
 
Language English
 
Relation Not Available;
 
Publisher Taylor & Francis