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spTimer (version 0.6)

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

0.6

License

GPL (>= 2)

Maintainer

Khandoker Shuvo Bakar

Last Published

March 1st, 2013

Functions in spTimer (0.6)

Ozone concentration data used in Model validations for spatial interpolation.

Ozone concentration data used for Model fitting.

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

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

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

spTimer-internal

Service functions and some undocumented functions for the spTimer library

Initial values for the spatio-temporal models.

spTimer-package

Spatio-Temporal Bayesian Modelling using R

MCMC sampling for the spatio-temporal models.

Priors for the spatio-temporal models.

Plots for spTimer output.

spT.check.locations

Distance Monitoring Function

Summary statistics of the parameters.

spT.segment.plot

Utility plot for prediction/forecast

Geodetic/geodesic Distance

spT.data.selection

Selection of Spatial data from a big dataset.

Nominal Coverage

Choice for sampling spatial decay parameter $\phi$.

Validation Commands

spT.keep.morethan.dist

Present one coordinate in a defined area for presentation

Spatial and temporal predictions for the spatio-temporal models.

spT.grid.coords

Grid Coordinates

Timer series information.