Package: gcKrig 1.1.8
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:
gcKrig_1.1.8.tar.gz
gcKrig_1.1.8.tar.gz(r-4.5-noble)gcKrig_1.1.8.tar.gz(r-4.4-noble)
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 = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- 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
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:5ba8e0a267. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 09 2024 |
R-4.5-linux-x86_64 | OK | Dec 09 2024 |
Exports:beta.gcbinomial.gccorrTGFHUBdiscretegaussian.gcgm.gcmatern.gcmlegcmvnintGHKnegbin.gcplotgcpoisson.gcpowerexp.gcpredgcsimgcspherical.gcweibull.gczip.gc
Dependencies:RcppRcppArmadillo