| spate-package | Spatio-temporal modeling of large data with the spectral SPDE approach |
| 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 space of the SPDE. |
| 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. |
| 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 alpha. |
| 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. |
| post.dist.hist | Histogram of posterior distributions. |
| 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 epsilon. hyperparameter. |
| Ptau2 | Prior for nugget effect parameter tau2. |
| Pzeta | Prior for damping parameter zeta. |
| 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. |
| sample.four.coef | Sample from the full conditional of the Fourier coefficients. |
| spate | Spatio-temporal modeling of large data with the spectral SPDE approach |
| spate.init | Constructor for 'spateFT' object which are used for the two-dimensional Fourier transform. |
| spate.mcmc | MCMC algorithm for fitting the model. |
| spate.plot | Plot a spatio-temporal field. |
| spate.predict | Obtain samples from predictive distribution in space and time. |
| spate.sim | Simulate from the SPDE. |
| spateMCMC | 'spateMCMC' object output obtained from 'spate.mcmc'. |
| spateMLE | Maximum likelihood estimate for SPDE model with Gaussian observations. |
| 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. |