Package: gcKrig 1.1.8

Zifei Han

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>.

Authors:Zifei Han

gcKrig_1.1.8.tar.gz
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gcKrig_1.1.8.tgz(r-4.4-emscripten)gcKrig_1.1.8.tgz(r-4.3-emscripten)
gcKrig.pdf |gcKrig.html✨
gcKrig/json (API)

# Install 'gcKrig' in R:
install.packages('gcKrig', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • AtlanticFish - Dataset of Mid-Atlantic Highlands Fish
  • LansingTrees - Locations and Botanical Classification of Trees in Lansing Woods
  • OilWell - Location of Successful and Dry Wells
  • Weed95 - Counts of Weed Plants on a Field

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.00 score 1 stars 403 downloads 18 exports 2 dependencies

Last updated 3 years agofrom:5ba8e0a267. Checks:2 OK, 1 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 09 2025
R-4.5-linux-x86_64OKMar 09 2025
R-4.4-linux-x86_64NOTEMar 09 2025

Exports:beta.gcbinomial.gccorrTGFHUBdiscretegaussian.gcgm.gcmatern.gcmlegcmvnintGHKnegbin.gcplotgcpoisson.gcpowerexp.gcpredgcsimgcspherical.gcweibull.gczip.gc

Dependencies:RcppRcppArmadillo

Citation

To cite gcKrig in publications use:

Han Z, De Oliveira V (2018). “gcKrig: An R Package for the Analysis of Geostatistical Count Data Using Gaussian Copulas.” Journal of Statistical Software, 87(13), 1–32. doi:10.18637/jss.v087.i13.

Corresponding BibTeX entry: 

  @Article{,
    title = {{gcKrig}: An {R} Package for the Analysis of
      Geostatistical Count Data Using {G}aussian Copulas},
    author = {Zifei Han and Victor {De Oliveira}},
    journal = {Journal of Statistical Software},
    year = {2018},
    volume = {87},
    number = {13},
    pages = {1--32},
    doi = {10.18637/jss.v087.i13},
  }

Readme and manuals

Help Manual

Help pageTopics
Dataset of Mid-Atlantic Highlands FishAtlanticFish
The Beta Marginal of Class 'marginal.gc'beta.gc
The Binomial Marginal of Class 'marginal.gc'binomial.gc
Spatial Correlation Functions for Simulation, Likelihood Inference and Spatial Prediction in Gaussian Copula Models with Geostatistical Count Datacorr.gc
Compute the Correlation in Transformed Gaussian Random FieldscorrTG
Compute the Frechet Hoeffding Upper Bound for Given Discrete Marginal DistributionsFHUBdiscrete
The Gaussian Marginal of Class 'marginal.gc'gaussian.gc
The Gamma Marginal of Class 'marginal.gc'gm.gc
Locations and Botanical Classification of Trees in Lansing WoodsLansingTrees
Marginals for Data Simulation, Correlation Assessment, Likelihood Inference and Spatial Prediction in Gaussian Copula Models for Geostatistical Datamarginal.gc
The Matern Correlation Function of Class 'corr.gc'matern.gc
Maximum Likelihood Estimation in Gaussian Copula Models for Geostatistical Count Datamlegc
Computing Multivariate Normal Rectangle ProbabilitymvnintGHK
The Negative Binomial Marginal of Class 'marginal.gc'negbin.gc
Location of Successful and Dry WellsOilWell
Plot Geostatistical Data and Fitted Meanplot.mlegc
Plot Geostatistical Data at Sampling and Prediction Locationsplot.predgc
Plot Geostatistical Data Simulated From Gaussian Copulaplot.simgc
Plot Geostatistical Count Dataplotgc
The Poisson Marginal of Class 'marginal.gc'poisson.gc
The Powered Exponential Correlation Function of Class 'corr.gc'powerexp.gc
Prediction at Unobserved Locations in Gaussian Copula Models for Geostatistical Count Datapredgc
Profile Likelihood Based Confidence Interval of Parameters for Gaussian Copula Models in Geostatistical Count Dataprofile.mlegc
Simulate Geostatistical Data from Gaussian Copula Model at Given Locationssimgc
The Spherical Correlation Function of Class 'corr.gc'spherical.gc
Methods for Extracting Information from Fitted Object of Class 'mlegc'print.mlegc print.summary.mlegc summary.mlegc
Methods for Extracting Information from Fitted Object of Class 'predgc'summary.predgc
Covariance Matrix of the Maximum Likelihood Estimatesvcov.mlegc
Counts of Weed Plants on a FieldWeed95
The Weibull Marginal of Class 'marginal.gc'weibull.gc
The Zero-inflated Poisson Marginal of Class 'marginal.gc'zip.gc