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:	1.2.7
Depends:	R (≥ 3.1.2)
Imports:	stats, graphics, ellipse, fields, MASS, plotrix, StatMatch
Published:	2021-01-16
Author:	Mark D. Risser [aut, cre]
Maintainer:	Mark D. Risser <markdrisser at gmail.com>
License:	MIT + file LICENSE
URL:	http://github.com/markdrisser/convoSPAT
NeedsCompilation:	no
Citation:	convoSPAT citation info
CRAN checks:	convoSPAT results

Documentation:

Reference manual:

convoSPAT.pdf

Downloads:

Package source:	convoSPAT_1.2.7.tar.gz
Windows binaries:	r-devel: convoSPAT_1.2.7.zip, r-release: convoSPAT_1.2.7.zip, r-oldrel: convoSPAT_1.2.7.zip
macOS binaries:	r-release (arm64): convoSPAT_1.2.7.tgz, r-oldrel (arm64): convoSPAT_1.2.7.tgz, r-release (x86_64): convoSPAT_1.2.7.tgz, r-oldrel (x86_64): convoSPAT_1.2.7.tgz
Old sources:	convoSPAT archive

Linking:

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