Approximate Gaussian Processes Using the Fourier Basis
Adds coefficient block structure to a spectral GP object
Calculates prior variances of coefficients in a spectral GP object
Changes correlation function parameter values of a spectral GP object
Copy a spectral GP object.
Calculate grid locations for a spectral GP object.
Calculates the gridpoints in a spectral GP object
Samples new coeffients via Gibbs sampling in a spectral GP object.
Create a new GP object
Calculates Hastings value of coefficients
Draws image plot with a legend strip for the color scale.
Test if object is a spectral GP
Add a line plot for a one-dimensional process based on a spectral GP o...
Calculates log prior density of a spectral GP object
Projects lon/lat coordinates to x/y Euclidean coordinate system
Matern correlation spectral density function
The names of the elements of a GP object
Map arbitrary locations to gridpoints of spectral GP object
Plot a process based on a spectral GP object
Add points for a one-dimensional process based on a spectral GP object
Prediction from a spectral GP object
Spectral GP default print statement
Proposes new coeffients in a spectral GP object.
Great circle distance matrix
Simulates a process realization from a spectral GP object
spectralGP generic functions
spectralGP - tools for specifying Gaussian processes using the computa...
Recalculate process values in a spectral GP object
Scales locations to the unit hypercube for use in spectral GP
Sets coefficients to zero in a spectral GP object
Routines for creating, manipulating, and performing Bayesian inference about Gaussian processes in one and two dimensions using the Fourier basis approximation: simulation and plotting of processes, calculation of coefficient variances, calculation of process density, coefficient proposals (for use in MCMC). It uses R environments to store GP objects as references/pointers.