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

This is the source code for the spate R package.

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Version

Install

install.packages('spate')

Monthly Downloads

224

Version

1.7.5

License

GPL-2

Maintainer

Fabio Sigrist

Last Published

October 3rd, 2023

Functions in spate (1.7.5)

print.spateMCMC

Print function for spateMCMC objects.
map.obs.to.grid

Maps non-gridded data to a grid.
print.spateSim

Print function for 'spateSim' objects.
summary.spateSim

Summary function for 'spateSim' objects.
real.fft

Fast calculation of the two-dimensional real Fourier transform.
real.fft.TS

Fast calculation of the two-dimensional real Fourier transform of a space-time field. For each time point, the spatial field is transformed.
spateMLE.RData

Maximum likelihood estimate for SPDE model with Gaussian observations.
propagate.spectral

Function that propagates a state (spectral coefficients).
spate.sim

Simulate from the SPDE.
lin.pred

Linear predictor.
spateMCMC.RData

'spateMCMC' object output obtained from 'spate.mcmc'.
tobit.lambda.log.full.cond

Full conditional for transformation parameter lambda.
spate.predict

Obtain samples from predictive distribution in space and time.
spate.plot

Plot a spatio-temporal field.
loglike

Log-likelihood of the hyperparameters.
sample.four.coef

Sample from the full conditional of the Fourier coefficients.
matern.spec

Spectrum of the Matern covariance function.
get.propagator

Propagator matrix G.
cols

Function that returns the color scale for 'image()'.
mcmc.summary

Summary function for MCMC output.
wave.numbers

Wave numbers.
spate-package

Spatio-temporal modeling of large data with the spectral SPDE approach
plot.spateMCMC

Plot fitted spateMCMC objects.
spate.init

Constructor for 'spateFT' object which are used for the two-dimensional Fourier transform.
get.propagator.vec

Propagator matrix G in vector form.
trace.plot

Trace plots for MCMC output analysis.
spate.mcmc

MCMC algorithm for fitting the model.
vect.to.TSmat

Converts a stacked vector into matrix.
vnorm

Eucledian norm of a vector
Palpha

Prior for direction of anisotropy in diffusion parameter alpha.
Plambda

Prior for transformation parameter of the Tobit model.
Psigma2

Prior for for variance parameter sigma2 of innovation epsilon. hyperparameter.
Pmuy

Prior for y-component of drift.
Ptau2

Prior for nugget effect parameter tau2.
Pzeta

Prior for damping parameter zeta.
Prho1

Prior for range parameter rho1 of diffusion.
Prho0

Prior for range parameter rho0 of innovation epsilon.
Pgamma

Prior for amount of anisotropy in diffusion parameter gamma.
Pmux

Prior for y-component of drift.
ffbs

Forward Filtering Backward Sampling algorithm.
index.complex.to.real.dft

Auxilary function for the real Fourier transform.
innov.spec

Spectrum of the innovation term epsilon.
ffbs.spectral

Forward Filtering Backward Sampling algorithm in the spectral space of the SPDE.
TSmat.to.vect

Converts a matrix stacked vector.
get.real.dft.mat

Matrix applying the two-dimensional real Fourier transform.
post.dist.hist

Histogram of posterior distributions.
plot.spateSim

Plotting function for 'spateSim' objects.