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: | 1.2.4 |
| Depends: | R (≥ 3.1.2) |
| Imports: | stats, graphics, ellipse, fields, geoR, MASS, plotrix, StatMatch |
| Published: | 2017-11-03 |
| 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 |
| Reference manual: | convoSPAT.pdf |
| Package source: | convoSPAT_1.2.4.tar.gz |
| Windows binaries: | r-devel: convoSPAT_1.2.4.zip, r-release: convoSPAT_1.2.4.zip, r-oldrel: convoSPAT_1.2.4.zip |
| OS X El Capitan binaries: | r-release: convoSPAT_1.2.4.tgz |
| OS X Mavericks binaries: | r-oldrel: convoSPAT_1.2.4.tgz |
| Old sources: | convoSPAT archive |
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