spate: Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach
Version 1.5

Functionality for spatio-temporal modeling of large data sets is provided. A Gaussian process in space and time is defined through a stochastic partial differential equation (SPDE). The SPDE is solved in the spectral space, and after discretizing in time and space, a linear Gaussian state space model is obtained. When doing inference, the main computational difficulty consists in evaluating the likelihood and in sampling from the full conditional of the spectral coefficients, or equivalently, the latent space-time process. In comparison to the traditional approach of using a spatio-temporal covariance function, the spectral SPDE approach is computationally advantageous. This package aims at providing tools for two different modeling approaches. First, the SPDE based spatio-temporal model can be used as a component in a customized hierarchical Bayesian model (HBM). The functions of the package then provide parameterizations of the process part of the model as well as computationally efficient algorithms needed for doing inference with the HBM. Alternatively, the adaptive MCMC algorithm implemented in the package can be used as an algorithm for doing inference without any additional modeling. The MCMC algorithm supports data that follow a Gaussian or a censored distribution with point mass at zero. Covariates can be included in the model through a regression term.

AuthorFabio Sigrist, Hans R. Kuensch, Werner A. Stahel
Date of publication2016-08-29 19:29:37
MaintainerFabio Sigrist <sigrist@stat.math.ethz.ch>
LicenseGPL-2
Version1.5
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("spate")

Getting started

Package overview

Popular man pages

cols: Function that returns the color scale for 'image()'.
ffbs: Forward Filtering Backward Sampling algorithm.
get.propagator: Propagator matrix G.
Plambda: Prior for transformation parameter of the Tobit model.
Psigma2: Prior for for variance parameter sigma2 of innovation...
sample.four.coef: Sample from the full conditional of the Fourier coefficients.
wave.numbers: Wave numbers.
See all...

All man pages Function index File listing

Man pages

cols: Function that returns the color scale for 'image()'.
ffbs: Forward Filtering Backward Sampling algorithm.
ffbs.spectral: Forward Filtering Backward Sampling algorithm in the spectral...
get.propagator: Propagator matrix G.
get.propagator.vec: Propagator matrix G in vector form.
get.real.dft.mat: Matrix applying the two-dimensional real Fourier transform.
hist.post.dist: Histogram of posterior distributions.
index.complex.to.real.dft: Auxilary function for the real Fourier transform.
innov.spec: Spectrum of the innovation term epsilon.
lin.pred: Linear predictor.
loglike: Log-likelihood of the hyperparameters.
map.obs.to.grid: Maps non-gridded data to a grid.
matern.spec: Spectrum of the Matern covariance function.
mcmc.summary: Summary function for MCMC output.
Palpha: Prior for direction of anisotropy in diffusion parameter...
Pgamma: Prior for amount of anisotropy in diffusion parameter gamma.
Plambda: Prior for transformation parameter of the Tobit model.
plot.spateMCMC: Plot fitted spateMCMC objects.
plot.spateSim: Plotting function for 'spateSim' objects.
Pmux: Prior for y-component of drift.
Pmuy: Prior for y-component of drift.
Prho0: Prior for range parameter rho0 of innovation epsilon.
Prho1: Prior for range parameter rho1 of diffusion.
print.spateMCMC: Print function for spateMCMC objects.
print.spateSim: Print function for 'spateSim' objects.
propagate.spectral: Function that propagates a state (spectral coefficients).
Psigma2: Prior for for variance parameter sigma2 of innovation...
Ptau2: Prior for nugget effect parameter tau2.
Pzeta: Prior for damping parameter zeta.
real.fft: Fast calculation of the two-dimensional real Fourier...
real.fft.TS: Fast calculation of the two-dimensional real Fourier...
sample.four.coef: Sample from the full conditional of the Fourier coefficients.
spate.init: Constructor for 'spateFT' object which are used for the...
spate.mcmc: MCMC algorithm for fitting the model.
spateMCMC: 'spateMCMC' object output obtained from 'spate.mcmc'.
spateMLE: Maximum likelihood estimate for SPDE model with Gaussian...
spate-package: Spatio-temporal modeling of large data with the spectral SPDE...
spate.plot: Plot a spatio-temporal field.
spate.predict: Obtain samples from predictive distribution in space and...
spate.sim: Simulate from the SPDE.
summary.spateSim: Summary function for 'spateSim' objects.
tobit.lambda.log.full.cond: Full conditional for transformation parameter lambda.
trace.plot: Trace plots for MCMC output analysis.
TSmat.to.vect: Converts a matrix stacked vector.
vect.to.TSmat: Converts a stacked vector into matrix.
vnorm: Eucledian norm of a vector
wave.numbers: Wave numbers.

Functions

Palpha Man page Source code
Pgamma Man page Source code
Plambda Man page Source code
Pmux Man page Source code
Pmuy Man page Source code
Prho0 Man page Source code
Prho1 Man page Source code
Psigma2 Man page Source code
Ptau2 Man page Source code
Pzeta Man page Source code
TSmat.to.vect Man page Source code
cols Man page Source code
ffbs Man page Source code
ffbs.spectral Man page Source code
get.propagator Man page Source code
get.propagator.vec Man page Source code
get.real.dft.mat Man page Source code
index.complex.to.real.dft Man page Source code
innov.spec Man page Source code
lin.pred Man page Source code
loglike Man page Source code
map.obs.to.grid Man page Source code
matern.spec Man page Source code
mcmc.summary Man page Source code
plot.spateMCMC Man page Source code
plot.spateSim Man page Source code
post.dist.hist Man page Source code
print.spateMCMC Man page Source code
print.spateSim Man page Source code
propagate.spectral Man page Source code
real.fft Man page Source code
real.fft.TS Man page Source code
sample.four.coef Man page Source code
spate Man page
spate-package Man page
spate.init Man page Source code
spate.mcmc Man page Source code
spate.plot Man page Source code
spate.predict Man page Source code
spate.sim Man page Source code
spateMCMC Man page
spateMLE Man page
summary.spateSim Man page Source code
tobit.lambda.log.full.cond Man page Source code
trace.plot Man page Source code
vect.to.TSmat Man page Source code
vnorm Man page Source code
wave.numbers Man page Source code

Files

inst
inst/CITATION
inst/doc
inst/doc/spate_tutorial.Rnw
inst/doc/spate_tutorial.pdf
inst/doc/spate_tutorial.R
configure.ac
src
src/Makevars.in
src/ffbs.spectral.c
src/Makevars.win
NAMESPACE
data
data/spateMLE.RData
data/spateMCMC.RData
R
R/spateFcts.R
vignettes
vignettes/spate_tutorial-FourierBasis2.pdf
vignettes/spate_tutorial.Rnw
vignettes/spate_tutorial-Propagator.pdf
MD5
build
build/vignette.rds
DESCRIPTION
configure
man
man/Pmuy.Rd
man/Pmux.Rd
man/Palpha.Rd
man/mcmc.summary.Rd
man/matern.spec.Rd
man/propagate.spectral.Rd
man/Prho0.Rd
man/innov.spec.Rd
man/spateMLE.Rd
man/Prho1.Rd
man/real.fft.TS.Rd
man/Pzeta.Rd
man/get.real.dft.mat.Rd
man/loglike.Rd
man/tobit.lambda.log.full.cond.Rd
man/real.fft.Rd
man/TSmat.to.vect.Rd
man/cols.Rd
man/Psigma2.Rd
man/Ptau2.Rd
man/spate.predict.Rd
man/summary.spateSim.Rd
man/hist.post.dist.Rd
man/sample.four.coef.Rd
man/plot.spateSim.Rd
man/trace.plot.Rd
man/lin.pred.Rd
man/plot.spateMCMC.Rd
man/map.obs.to.grid.Rd
man/spate.mcmc.Rd
man/spate.sim.Rd
man/vect.to.TSmat.Rd
man/vnorm.Rd
man/spateMCMC.Rd
man/ffbs.Rd
man/Pgamma.Rd
man/spate.init.Rd
man/get.propagator.vec.Rd
man/spate-package.Rd
man/print.spateMCMC.Rd
man/wave.numbers.Rd
man/Plambda.Rd
man/index.complex.to.real.dft.Rd
man/get.propagator.Rd
man/spate.plot.Rd
man/ffbs.spectral.Rd
man/print.spateSim.Rd
configure.win
cleanup
tools
tools/aclocal.m4
spate documentation built on May 19, 2017, 8:48 a.m.

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