Package: spTimer 3.3.3

K. Shuvo Bakar

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:K. Shuvo Bakar [aut, cre], Sujit K. Sahu [ctb]

spTimer_3.3.3.tar.gz
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.pdf |spTimer.html
spTimer/json (API)

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

Peer review:

Datasets:
  • NYdata - Observations of ozone concentration levels, maximum temperature and wind speed.
  • NYgrid - Observations of ozone concentration levels, maximum temperature and wind speed.

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

2.90 score 2 stars 2 packages 66 scripts 556 downloads 1 mentions 29 exports 9 dependencies

Last updated 4 months agofrom:accc4053f8. Checks:2 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKJan 07 2025
R-4.5-linux-x86_64OKJan 07 2025

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