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Local spatial-predictor selection

Conference Paper


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Abstract


  • Consider the problem of spatial prediction of a random process from a spatial dataset. Global spatial-predictor selection provides a way to choose a single spatial predictor from a number of competing predictors. Instead, we consider local spatial-predictor selection at each spatial location in the domain of interest. This results in a hybrid predictor that could be considered global, since it takes the form of a combination of local predictors; we call this the locally selected spatial predictor. We pursue this idea here using the (empirical) deviance information as our criterion for (global and local) predictor selection. In a small simulation study, the relative performance of this combined predictor, relative to the individual predictors, is assessed.

Authors


  •   Bradley, J R. (external author)
  •   Cressie, Noel A.
  •   Shi, Tao (external author)

Publication Date


  • 2012

Citation


  • Bradley, J., Cressie, N. & Shi, T. (2012). Local spatial-predictor selection. 2012 Proceedings of the Joint Statistical Meetings (pp. 3098-3110). Alexandra, United States: American Statistical Association.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1113&context=cssmwp

Ro Metadata Url


  • http://ro.uow.edu.au/cssmwp/119

Start Page


  • 3098

End Page


  • 3110

Place Of Publication


  • http://www.amstat.org/meetings/jsm/2012/program.cfm

Abstract


  • Consider the problem of spatial prediction of a random process from a spatial dataset. Global spatial-predictor selection provides a way to choose a single spatial predictor from a number of competing predictors. Instead, we consider local spatial-predictor selection at each spatial location in the domain of interest. This results in a hybrid predictor that could be considered global, since it takes the form of a combination of local predictors; we call this the locally selected spatial predictor. We pursue this idea here using the (empirical) deviance information as our criterion for (global and local) predictor selection. In a small simulation study, the relative performance of this combined predictor, relative to the individual predictors, is assessed.

Authors


  •   Bradley, J R. (external author)
  •   Cressie, Noel A.
  •   Shi, Tao (external author)

Publication Date


  • 2012

Citation


  • Bradley, J., Cressie, N. & Shi, T. (2012). Local spatial-predictor selection. 2012 Proceedings of the Joint Statistical Meetings (pp. 3098-3110). Alexandra, United States: American Statistical Association.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1113&context=cssmwp

Ro Metadata Url


  • http://ro.uow.edu.au/cssmwp/119

Start Page


  • 3098

End Page


  • 3110

Place Of Publication


  • http://www.amstat.org/meetings/jsm/2012/program.cfm