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spTimer (version 0.8)

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.

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Version

Install

install.packages('spTimer')

Monthly Downloads

544

Version

0.8

License

GPL (>= 2)

Maintainer

Khandoker Shuvo Bakar

Last Published

July 4th, 2013

Functions in spTimer (0.8)

spT.data.selection

Selection of Spatial data from a big dataset.
spT.Gibbs

MCMC sampling for the spatio-temporal models.
spT.decay

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

Plots for spTimer output.
spT.keep.morethan.dist

Present one coordinate in a defined area for presentation
NYdata

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

Nominal Coverage
spT.grid.coords

Grid Coordinates
spT.segment.plot

Utility plot for prediction/forecast
spT.time

Timer series information.
spT.check.locations

Distance Monitoring Function
spTimer-package

Spatio-Temporal Bayesian Modelling using R
summary.spT

Summary statistics of the parameters.
spT.initials

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

Validation Commands
predict.spT

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

Geodetic/geodesic Distance
spT.priors

Priors for the spatio-temporal models.
spTimer-internal

Service functions and some undocumented functions for the spTimer library
as.forecast.object

Conversion of spT object into forecast object