An empirical likelihood method for spatial regression |
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Authors: | Daniel J Nordman |
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Institution: | (1) Department of Statistics, Iowa State University, Ames, IA 50011, USA |
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Abstract: | Properties of a “blockwise”empirical likelihood for spatial regression with non-stochastic regressors are investigated for
spatial data on a lattice. The method enables nonparametric confidence regions for spatial trend parameters to be calibrated,
even though non-random regressors introduce non-stationary forms of spatial dependence into the “blockwise” construction. Additionally, the regression results are valid in a general
framework allowing for a variety of behavior in regressor variables as well as the underlying spatial error process. The same
regression method also applies when the regressors are stochastic. |
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Keywords: | Blocking Spatial lattice data Non-stationarity Non-stochastic regressors |
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