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 |
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Creator |
Nobin Chandra Paul
Anil Rai Tauqueer Ahmad Ankur Biswas Prachi Misra Sahoo |
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Subject |
Data integration
geographically weighted regression model-assisted approach spatial non-stationarity two-phase regression |
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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 |
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Date |
2023-11-22T12:23:52Z
2023-11-22T12:23:52Z 2023-11-14 |
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Type |
Research Paper
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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 |
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Language |
English
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Relation |
Not Available;
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Publisher |
Taylor & Francis
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