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Spatial estimation and rescaled spatial bootstrap approach for finite population
Authors:Ankur Biswas  Anil Rai  Tauqueer Ahmad  Prachi Misra Sahoo
Institution:1. Division of Sample Surveys, ICAR-Indian Agricultural Statistics Research Institute (ICAR-IASRI), New Delhi, India;2. Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute (ICAR-IASRI), New Delhi, India
Abstract:In this study, an attempt has been made to improve the sampling strategy incorporating spatial dependency at estimation stage considering usual aerial sampling scheme, such as simple random sampling, when the underlying population is finite and spatial in nature. Using the distances between spatial units, an improved method of estimation, viz. spatial estimation procedure, has been proposed for the estimation of finite population mean. Further, rescaled spatial bootstrap (RSB) methods have been proposed for approximately unbiased estimation of variance of the proposed spatial estimator (SE). The properties of the proposed SE and its corresponding RSB methods were studied empirically through simulation.
Keywords:Inverse distance weighting  Prediction approach  Rescaled spatial bootstrap  Spatial data  Spatial estimator  
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