convoSPAT (1.2.6)

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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.

Maintainer: Mark D. Risser
Author(s): Mark D. Risser [aut, cre]

License: MIT + file LICENSE

Uses: ellipse, fields, MASS, plotrix, StatMatch

Released 26 days ago.

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