Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Local Likelihood Estimation for Covariance Functions with Spatially-Varying Parameters: The convoSPAT Package for R | Risser | Journal of Statistical Software
Authors: Mark D. Risser, Catherine A. Calder
Title: Local Likelihood Estimation for Covariance Functions with Spatially-Varying Parameters: The convoSPAT Package for R
Abstract: In spite of the interest in and appeal of convolution-based approaches for nonstationary spatial modeling, off-the-shelf software for model fitting does not as of yet exist. Convolution-based models are highly flexible yet notoriously difficult to fit, even with relatively small data sets. The general lack of pre-packaged options for model fitting makes it difficult to compare new methodology in nonstationary modeling with other existing methods, and as a result most new models are simply compared to stationary models. Using a convolution-based approach, we present a new nonstationary covariance function for spatial Gaussian process models that allows for efficient computing in two ways: first, by representing the spatially-varying parameters via a discrete mixture or "mixture component" model, and second, by estimating the mixture component parameters through a local likelihood approach. In order to make computations for a convolutionbased nonstationary spatial model readily available, this paper also presents and describes the convoSPAT package for R. The nonstationary model is fit to both a synthetic data set and a real data application involving annual precipitation to demonstrate the capabilities of the package.

Page views:: 169. Submitted: 2015-07-28. Published: 2017-11-13.
Paper: Local Likelihood Estimation for Covariance Functions with Spatially-Varying Parameters: The convoSPAT Package for R     Download PDF (Downloads: 41)
Supplements:
convoSPAT_1.2.4.tar.gz: R source package Download (Downloads: 3; 120KB)
v81i14.R: R replication code Download (Downloads: 4; 39KB)

DOI: 10.18637/jss.v081.i14

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