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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/23825

Title: Estimating the spatial covariance structure using the geoadditive model
Authors: Vandendijck, Yannick
Faes, Christel
Hens, Niel
Issue Date: 2017
Abstract: In geostatistics, both kriging and smoothing splines are commonly used to generate an interpolated map of a quantity of interest. The geoadditive model proposed by Kammann and Wand (J R Stat Soc: Ser C (Appl Stat) 52(1):1–18, 2003) represents a fusion of kriging and penalized spline additive models. Complex data issues, including non-linear covariate trends, multiple measurements at a location and clustered observations are easily handled using the geoadditive model. We propose a likelihood based estimation procedure that enables the estimation of the range (spatial decay) parameter associated with the penalized splines of the spatial component in the geoadditive model. We present how the spatial covariance structure (covariogram) can be derived from the geoadditive model. In a simulation study, we show that the underlying spatial process and prediction of the spatial map are estimated well using the proposed likelihood based estimation procedure. We present several applications of the proposed methods on real-life data examples.
Notes: Vandendijck, Y (reprint author), Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. Yannick.vandendijck@uhasselt.be
URI: http://hdl.handle.net/1942/23825
DOI: 10.1007/s10651-017-0373-3
ISI #: 000402165900008
ISSN: 1352-8505
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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