Comments on: Comparing and selecting spatial predictors using local criteria

Finn Lindgren

doi:10.1007/s11749-014-0417-z

Comments on: Comparing and selecting spatial predictors using local criteria

Finn Lindgren

Department of Mathematical Sciences

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Abstract

Large spatial data sets require innovative techniques for computationally efficient statistical estimation. In this comment some aspects of local predictor selection are explored, with a view towards spatially coherent field prediction and uncertainty quantification.

Original language	English
Pages (from-to)	35-44
Journal	Test
Volume	24
Issue number	1
Early online date	29 Nov 2014
DOIs	https://doi.org/10.1007/s11749-014-0417-z
Publication status	Published - Mar 2015

Keywords

Local model selection
Non-stationarity
Predictive scoring rules
Stochastic partial differential equation
Stochastic spatial models

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lindgren_acceptedAccepted author manuscript, 9.91 MB

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title = "Comments on: Comparing and selecting spatial predictors using local criteria",

abstract = "Large spatial data sets require innovative techniques for computationally efficient statistical estimation. In this comment some aspects of local predictor selection are explored, with a view towards spatially coherent field prediction and uncertainty quantification.",

keywords = "Local model selection, Non-stationarity, Predictive scoring rules, Stochastic partial differential equation, Stochastic spatial models",

author = "Finn Lindgren",

year = "2015",

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KW - Stochastic partial differential equation

KW - Stochastic spatial models

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Comments on: Comparing and selecting spatial predictors using local criteria

Abstract

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