convoSPAT: Convolution-Based Nonstationary Spatial Modeling

Fits convolution-based nonstationary Gaussian process models to point-referenced spatial data. The nonstationary covariance function allows the user to specify the underlying correlation structure and which spatial dependence parameters should be allowed to vary over space: the anisotropy, nugget variance, and process variance. The parameters are estimated via maximum likelihood, using a local likelihood approach. Also provided are functions to fit stationary spatial models for comparison, calculate the Kriging predictor and standard errors, and create various plots to visualize nonstationarity.

Version: 1.2
Depends: R (≥ 3.1.2)
Imports: stats, graphics, ellipse, fields, geoR, MASS, plotrix, StatMatch
Published: 2017-04-12
Author: Mark D. Risser [aut, cre]
Maintainer: Mark D. Risser <markdrisser at>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: convoSPAT results


Reference manual: convoSPAT.pdf
Package source: convoSPAT_1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: convoSPAT_1.2.tgz
OS X Mavericks binaries: r-oldrel: convoSPAT_1.2.tgz
Old sources: convoSPAT archive


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