Package: geostatsp 2.1.0
geostatsp: Geostatistical Modelling with Likelihood and Bayes
Geostatistical modelling facilities using 'SpatRaster' and 'SpatVector' objects are provided. Non-Gaussian models are fit using 'INLA', and Gaussian geostatistical models use Maximum Likelihood Estimation. For details see Brown (2015) <doi:10.18637/jss.v063.i12>. The 'RandomFields' package is available at <https://web.archive.org/web/20250719184025/https://www.wim.uni-mannheim.de/schlather/publications/software> and <https://github.com/cran/RandomFields>.
Authors:
geostatsp_2.1.0.tar.gz
geostatsp_2.1.0.zip(r-4.7-x86_64)geostatsp_2.1.0.zip(r-4.6-x86_64)geostatsp_2.1.0.zip(r-4.5-x86_64)
geostatsp_2.1.0.tgz(r-4.6-x86_64)geostatsp_2.1.0.tgz(r-4.6-arm64)geostatsp_2.1.0.tgz(r-4.5-x86_64)geostatsp_2.1.0.tgz(r-4.5-arm64)
geostatsp_2.1.0.tar.gz(r-4.7-arm64)geostatsp_2.1.0.tar.gz(r-4.7-x86_64)geostatsp_2.1.0.tar.gz(r-4.6-arm64)geostatsp_2.1.0.tar.gz(r-4.6-x86_64)
geostatsp_2.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
geostatsp/json (API)
| # Install 'geostatsp' in R: |
| install.packages('geostatsp', repos = c('https://eborgnine.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/diseasemapping
Datasets:
- elevationLoa - Loaloa prevalence data from 197 village surveys
- eviLoa - Loaloa prevalence data from 197 village surveys
- gambiaUTM - Gambia data
- loaloa - Loaloa prevalence data from 197 village surveys
- ltLoa - Loaloa prevalence data from 197 village surveys
- murder - Murder locations
- rongelapUTM - Rongelap data
- swissAltitude - Swiss rainfall data
- swissBorder - Swiss rainfall data
- swissLandType - Swiss rainfall data
- swissNN - Raster of Swiss rain data
- swissRain - Swiss rainfall data
- swissRainR - Raster of Swiss rain data
- tempLoa - Loaloa prevalence data from 197 village surveys
- torontoBorder - Murder locations
- torontoIncome - Murder locations
- torontoNight - Murder locations
- torontoPdens - Murder locations
- wheat - Mercer and Hall wheat yield data
Last updated from:15f8b7304f. Checks:4 ERROR, 2 NOTE, 7 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | ERROR | 288 | ||
| linux-devel-x86_64 | NOTE | 338 | ||
| source / vignettes | OK | 241 | ||
| linux-release-arm64 | ERROR | 302 | ||
| linux-release-x86_64 | OK | 374 | ||
| macos-release-arm64 | OK | 376 | ||
| macos-release-x86_64 | OK | 516 | ||
| macos-oldrel-arm64 | ERROR | 174 | ||
| macos-oldrel-x86_64 | ERROR | 403 | ||
| windows-devel-x86_64 | NOTE | 407 | ||
| windows-release-x86_64 | OK | 418 | ||
| windows-oldrel-x86_64 | OK | 436 | ||
| wasm-release | OK | 673 |
Exports:conditionalGmrfexcProbfillParamglgminformationLgminla.modelskrigeLgmlgcplgmlikfitLgmloglikLgmmaternmaternGmrfPrecmodelRandomFieldsNNmatpcPriorRangepostExpprofLlgmRFsimulatesimLgcpsimPoissonPPspatialRocspdfToBricksquareRasterstackRasterListvariogvariogMcEnv
LGCP with PC priors
Last update: 2024-05-24
Started: 2016-02-18
Various GLGM examples
Last update: 2024-02-13
Started: 2017-07-26
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Conditional distribution of GMRF | conditionalGmrf |
| Exceedance probabilities | excProb |
| Gambia data | gambiaUTM |
| Generalized Linear Geostatistical Models | glgm glgm,ANY,ANY,ANY,ANY-method glgm,formula,data.frame,SpatRaster,data.frame-method glgm,formula,SpatRaster,ANY,ANY-method glgm,formula,SpatVector,ANY,ANY-method glgm-methods lgcp |
| Valid models in INLA | inla.models |
| Spatial prediction, or Kriging | krigeLgm |
| Linear Geostatistical Models | lgm lgm,character,ANY,ANY,ANY-method lgm,formula,data.frame,SpatRaster,data.frame-method lgm,formula,SpatRaster,ANY,ANY-method lgm,formula,SpatVector,numeric,ANY-method lgm,formula,SpatVector,SpatRaster,data.frame-method lgm,formula,SpatVector,SpatRaster,list-method lgm,formula,SpatVector,SpatRaster,missing-method lgm,formula,SpatVector,SpatRaster,SpatRaster-method lgm,missing,ANY,ANY,ANY-method lgm,numeric,ANY,ANY,ANY-method lgm-methods |
| Likelihood Based Parameter Estimation for Gaussian Random Fields | likfitLgm loglikLgm |
| Loaloa prevalence data from 197 village surveys | elevationLoa eviLoa loaloa ltLoa tempLoa |
| Evaluate the Matern correlation function | fillParam matern matern.default matern.dist matern.SpatRaster matern.SpatVector |
| Precision matrix for a Matern spatial correlation | maternGmrfPrec maternGmrfPrec.default maternGmrfPrec.dgCMatrix NNmat NNmat.default NNmat.SpatRaster |
| Murder locations | murder torontoBorder torontoIncome torontoNight torontoPdens |
| PC prior for range parameter | pcPrior pcPriorRange |
| Exponentiate posterior quantiles | postExp |
| Joint confidence regions | informationLgm profLlgm |
| Simulation of Random Fields | modelRandomFields RFsimulate RFsimulate,ANY,SpatRaster-method RFsimulate,data.frame,ANY-method RFsimulate,matrix,SpatRaster-method RFsimulate,matrix,SpatVector-method RFsimulate,numeric,SpatRaster-method RFsimulate,numeric,SpatVector-method RFsimulate,RMmodel,SpatRaster-method RFsimulate,RMmodel,SpatVector-method RFsimulate-methods |
| Rongelap data | rongelapUTM |
| Simulate a log-Gaussian Cox process | simLgcp simPoissonPP |
| Sensitivity and specificity | spatialRoc |
| Create a raster with square cells | squareRaster squareRaster,matrix-method squareRaster,SpatExtent-method squareRaster,SpatRaster-method squareRaster,SpatVector-method squareRaster-methods |
| Converts a list of rasters, possibly with different projections and resolutions, to a single raster stack. | spdfToBrick stackRasterList |
| Swiss rainfall data | swissAltitude swissBorder swissLandType swissRain |
| Raster of Swiss rain data | swissNN swissRainR |
| Compute Empirical Variograms and Permutation Envelopes | variog variog.default variog.SpatVector variogMcEnv variogMcEnv.default variogMcEnv.SpatVector |
| Mercer and Hall wheat yield data | wheat |
