spTimer v3.3


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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>.

Functions in spTimer

Name Description
spTimer-package Spatio-Temporal Bayesian Modelling using R
spT.validation2 Validation Commands
summary.spT Summary statistics of the parameters.
spT.priors Priors for the spatio-temporal models.
spT.pCOVER Nominal Coverage
spTimer-internal Service functions and some undocumented functions for the spTimer library
spT.segment.plot Utility plot for prediction/forecast
spT.subset Select a subset of Spatial data.
spT.time Timer series information.
plot.spT Plots for spTimer output.
spT.validation Validation Commands
fitted.spT Extract model fitted values.
spT.geodist Geodetic/geodesic Distance
spT.decay Choice for sampling spatial decay parameter \(\phi\).
spT.grid.coords Grid Coordinates
spT.initials Initial values for the spatio-temporal models.
NYdata Observations of ozone concentration levels, maximum temperature and wind speed.
confint.spT Credible intervals for model parameters.
predict.spT Spatial and temporal predictions for the spatio-temporal models.
spT.Gibbs MCMC sampling for the spatio-temporal models.
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Type Package
Date 2018-11-07
License GPL (>= 2)
LazyData yes
NeedsCompilation yes
Packaged 2018-11-06 23:41:50 UTC; bak18b
Repository CRAN
Date/Publication 2018-11-10 07:40:03 UTC

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