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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