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spTimer (version 0.02)

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

0.02

License

GPL (>= 2)

Maintainer

Khandoker Shuvo Bakar

Last Published

July 5th, 2012

Functions in spTimer (0.02)

NYdata

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

Timer series information.
spT.priors

Priors for the spatio-temporal models.
spT.initials

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

Predictions for the spatio-temporal models.
spT.Summary.Stat

Summary Statistics
spT.validation

Validation Commands
spT.pCOVER

Nominal Coverage
spT.geodist

Geodetic/geodesic Distance
spTimer-internal

Service functions and some undocumented functions for the spTimer library
spT.segment.plot

Utility plot for prediction/forecast
spT.data.selection

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

Forecast for the spatio-temporal models.
spT.grid.coords

Grid Coordinates
spT.MCMC.stat

MCMC summary for the posterior samples
spTimer-package

Spatio-Temporal Bayesian Modelling using R
spT.Gibbs

MCMC sampling for the spatio-temporal models.
spT.check.locations

Distance Monitoring Function
spT.decay

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

MCMC plots for the posterior samples
NYsite

Position of ozone monitoring sites in New York