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spTimer (version 1.0-2)

Spatio-Temporal Bayesian Modelling Using R

Description

The package is able to fit, spatially predict and temporally forecast 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 big-n problem.

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Version

Install

install.packages('spTimer')

Monthly Downloads

318

Version

1.0-2

License

GPL (>= 2)

Maintainer

Shuvo Bakar

Last Published

June 23rd, 2014

Functions in spTimer (1.0-2)

spTimer-internal

Service functions and some undocumented functions for the spTimer library
fitted.spT

Extract model fitted values.
predict.spT

Spatial and temporal predictions for the spatio-temporal models.
spT.time

Timer series information.
spT.check.locations

Distance Monitoring Function
spT.validation

Validation Commands
spT.geodist

Geodetic/geodesic Distance
spTimer-package

Spatio-Temporal Bayesian Modelling using R
spT.initials

Initial values for the spatio-temporal models.
spT.priors

Priors for the spatio-temporal models.
NYdata

Observations of ozone concentration levels, maximum temperature and wind speed.
spT.pCOVER

Nominal Coverage
spT.subset

Select a subset of Spatial data.
summary.spT

Summary statistics of the parameters.
spT.segment.plot

Utility plot for prediction/forecast
spT.keep.morethan.dist

Present one coordinate in a defined area for presentation
spT.grid.coords

Grid Coordinates
as.forecast.object

Conversion of spT object into forecast object
confint.spT

Credible intervals for model parameters.
plot.spT

Plots for spTimer output.
spT.decay

Choice for sampling spatial decay parameter $\phi$.
spT.Gibbs

MCMC sampling for the spatio-temporal models.