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Tip revision: 39619b937089a0eb784ec0c89162ffceebcb4700 authored by Mark D. Risser on 23 January 2020, 17:50 UTC
version 1.2.6
Tip revision: 39619b9
Package: convoSPAT
Type: Package
Title: Convolution-Based Nonstationary Spatial Modeling
Version: 1.2.6
Date: 2020-01-22
Authors@R: person("Mark D.", "Risser", email = "",
    role = c("aut", "cre"))
Description: 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.
Depends: R (>= 3.1.2)
License: MIT + file LICENSE
LazyData: TRUE
Imports: stats, graphics, ellipse, fields, MASS, plotrix, StatMatch
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-23 18:28:30 UTC; MDRisser
Author: Mark D. Risser [aut, cre]
Maintainer: Mark D. Risser <>
Repository: CRAN
Date/Publication: 2020-01-23 18:50:02 UTC
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