Package: ramps 0.6.18

ramps: Bayesian Geostatistical Modeling with RAMPS

Bayesian geostatistical modeling of Gaussian processes using a reparameterized and marginalized posterior sampling (RAMPS) algorithm designed to lower autocorrelation in MCMC samples. Package performance is tuned for large spatial datasets.

Authors:Brian J Smith [aut, cre], Jun Yan [aut], Mary Kathryn Cowles [aut]

ramps_0.6.18.tar.gz
ramps_0.6.18.zip(r-4.5)ramps_0.6.18.zip(r-4.4)ramps_0.6.18.zip(r-4.3)
ramps_0.6.18.tgz(r-4.4-any)ramps_0.6.18.tgz(r-4.3-any)
ramps_0.6.18.tar.gz(r-4.5-noble)ramps_0.6.18.tar.gz(r-4.4-noble)
ramps_0.6.18.tgz(r-4.4-emscripten)ramps_0.6.18.tgz(r-4.3-emscripten)
ramps.pdf |ramps.html
ramps/json (API)

# Install 'ramps' in R:
install.packages('ramps', repos = c('https://brian-j-smith.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • NURE - Dataset of USGS NURE Uranium Measurements
  • NURE.grid - Dataset of USGS NURE Uranium Measurements
  • simGrid - Dataset of Simulated Measurements from JSS Publication
  • simIowa - Dataset of Simulated Measurements from JSS Publication

On CRAN:

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

19 exports 0.00 score 10 dependencies 26 scripts 397 downloads

Last updated 2 years agofrom:af67bcc81f. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 16 2024
R-4.5-winOKSep 16 2024
R-4.5-linuxOKSep 16 2024
R-4.4-winOKSep 16 2024
R-4.4-macOKSep 16 2024
R-4.3-winOKSep 16 2024
R-4.3-macOKSep 16 2024

Exports:corRCauchycorRExpcorRExp2corRExpwrcorRExpwr2corRExpwr2DtcorRGauscorRGneitcorRLincorRMaterncorRSphercorRWaveDICexpand.chaingenUSStateGridgenUSStateSitesgeorampsparamramps.control

Dependencies:codadotCall64fieldslatticemapsMatrixnlmeRcppspamviridisLite

Readme and manuals