Package: spTimer 3.3.3
spTimer: Spatio-Temporal Bayesian Modelling
Fits, spatially predicts and temporally forecasts large amounts of space-time data using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models for spatio-temporal big-n problems. Bakar and Sahu (2015) <doi:10.18637/jss.v063.i15>.
Authors:
spTimer_3.3.3.tar.gz
spTimer_3.3.3.zip(r-4.5)spTimer_3.3.3.zip(r-4.4)spTimer_3.3.2.zip(r-4.3)
spTimer_3.3.3.tgz(r-4.4-x86_64)spTimer_3.3.3.tgz(r-4.4-arm64)spTimer_3.3.2.tgz(r-4.3-x86_64)spTimer_3.3.2.tgz(r-4.3-arm64)
spTimer_3.3.3.tar.gz(r-4.5-noble)spTimer_3.3.3.tar.gz(r-4.4-noble)
spTimer_3.3.3.tgz(r-4.4-emscripten)spTimer_3.3.2.tgz(r-4.3-emscripten)
spTimer.pdf |spTimer.html✨
spTimer/json (API)
# Install 'spTimer' in R: |
install.packages('spTimer', repos = c('https://ksbakar.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:accc4053f8. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 08 2024 |
R-4.5-win-x86_64 | OK | Nov 08 2024 |
R-4.5-linux-x86_64 | OK | Nov 08 2024 |
R-4.4-win-x86_64 | OK | Nov 08 2024 |
R-4.4-mac-x86_64 | OK | Nov 08 2024 |
R-4.4-mac-aarch64 | OK | Nov 08 2024 |
R-4.3-win-x86_64 | OK | Sep 08 2024 |
R-4.3-mac-x86_64 | OK | Sep 08 2024 |
R-4.3-mac-aarch64 | OK | Sep 08 2024 |
Exports:as.mcmc.spTcoef.spTconfint.spTfitted.spTFormula.coordsFormula.matrixformula.spTGammNormplot.spTpredict.spTprint.spTresiduals.spTspT.decayspT.geo_distspT.geo.distspT.geodistspT.GibbsspT.grid.coordsspT.initialsspT.pCOVERspT.priorsspT.segment.plotspT.subsetspT.timespT.validationspT.validation2summary.spTUnif
Dependencies:codaextraDistrintervalslatticeRcppspspacetimextszoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Spatio-Temporal Bayesian Modelling using R | spTimer-package spTimer |
Credible intervals for model parameters. | confint.spT |
Extract model fitted values. | fitted.spT |
Observations of ozone concentration levels, maximum temperature and wind speed. | NYdata NYgrid |
Plots for spTimer output. | plot.spT |
Spatial and temporal predictions for the spatio-temporal models. | predict.spT |
Choice for sampling spatial decay parameter phi. | spT.decay |
Geodetic/geodesic Distance | spT.geo.dist spT.geodist spT.geo_dist |
MCMC sampling for the spatio-temporal models. | spT.Gibbs |
Grid Coordinates | spT.grid.coords |
Initial values for the spatio-temporal models. | spT.initials |
Nominal Coverage | spT.pCOVER |
Priors for the spatio-temporal models. | spT.priors |
Utility plot for prediction/forecast | spT.segment.plot |
Select a subset of Spatial data. | spT.subset |
Timer series information. | spT.time |
Validation Commands | spT.validation |
Validation Commands | spT.validation2 |
Summary statistics of the parameters. | summary.spT |