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spTimer (version 0.05)

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

318

Version

0.05

License

GPL (>= 2)

Maintainer

Khandoker Shuvo Bakar

Last Published

January 22nd, 2013

Functions in spTimer (0.05)

spT.data.selection

Selection of Spatial data from a big dataset.

spTimer-internal

Service functions and some undocumented functions for the spTimer library

spT.check.locations

Distance Monitoring Function

MCMC sampling for the spatio-temporal models.

spT.grid.coords

Grid Coordinates

spT.keep.morethan.dist

Present one coordinate in a defined area for presentation

Validation Commands

Summary statistics of the parameters.

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

Initial values for the spatio-temporal models.

spT.segment.plot

Utility plot for prediction/forecast

Timer series information.

spTimer-package

Spatio-Temporal Bayesian Modelling using R

Ozone concentration data used in Model validations for temporal forecast in the unovserved spatial locations.

Ozone concentration data used in Model validations for temporal forecast in the ovserved spatial locations.

Ozone concentration data used for Model fitting.

Nominal Coverage

Ozone concentration data used in Model validations for spatial interpolation.

Choice for sampling spatial decay parameter $\phi$.

Priors for the spatio-temporal models.

Spatial and temporal predictions for the spatio-temporal models.

Geodetic/geodesic Distance

Plots for spTimer output.