gcKrig: Analysis of Geostatistical Count Data using Gaussian Copulas
Provides a variety of functions to analyze and model
    geostatistical count data with Gaussian copulas, including
 1) data simulation and visualization; 
 2) correlation structure assessment (here also known as the Normal To Anything); 
 3) calculate multivariate normal rectangle probabilities; 
 4) likelihood inference and parallel prediction at predictive locations.
 Description of the method is available from: Han and DeOliveira (2018) <doi:10.18637/jss.v087.i13>.
| Version: | 1.1.8 | 
| Depends: | R (≥ 3.2.5) | 
| Imports: | Rcpp (≥ 0.12.0) | 
| LinkingTo: | Rcpp, RcppArmadillo | 
| Suggests: | EQL, FNN, lattice, latticeExtra, mvtnorm, Matrix, MASS, numDeriv, scatterplot3d, snowfall, sp | 
| Published: | 2022-07-02 | 
| DOI: | 10.32614/CRAN.package.gcKrig | 
| Author: | Zifei Han | 
| Maintainer: | Zifei Han  <hanzifei1 at gmail.com> | 
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] | 
| NeedsCompilation: | yes | 
| Citation: | gcKrig citation info | 
| CRAN checks: | gcKrig results | 
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