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
DOI: 10.32614/CRAN.package.convoSPAT
Author: Mark D. Risser [aut, cre]
Maintainer: Mark D. Risser <markdrisser at>
License: MIT + file LICENSE
NeedsCompilation: no
Citation: convoSPAT citation info
CRAN checks: convoSPAT results


Reference manual: convoSPAT.pdf


Package source: convoSPAT_1.2.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


Please use the canonical form to link to this page.