mra_wendland_2d_pred: Code to construct the mutli-resolution sparse basis function...
In BayesMRA: Bayesian Multi-Resolution Gaussian Process Approximations

Description Usage Arguments Value Examples

Code to construct the mutli-resolution sparse basis function representation for fitting spatial processes

1	mra_wendland_2d_pred(locs, locs_pred, MRA, use_spam = TRUE)

`locs`	The location variables in 2 dimensions over which to construct the basis function representation in the fitting stage.
`locs_pred`	The location variables in 2 dimensions over which to construct the basis function representation in the prediction stage.
`MRA`	The multi-resolution basis expansion at the observed locations. This object is the output of `mra_wendland-2d()` and is of class "mra_wendland_2d".
`use_spam`	is a boolean flag to determine whether the output is a list of spam matrix objects (`use_spam = TRUE`) or a an n x n sparse Matrix of class "dgCMatrix" `use_spam = FALSE` (see spam and Matrix packages for details).

A list of objects including the MRA knots locations locs_grid, the Wendland basis representation matrix W_pred at the prediction locations, and the basis radius radius

set.seed(111)
locs <- matrix(runif(20), 10, 2)
locs_pred <- matrix(runif(20), 10, 2)
MRA <- mra_wendland_2d(locs, M = 2, n_coarse_grid = 4)
MRA_pred <- mra_wendland_2d_pred(locs, locs_pred, MRA)

## plot the MRA prediction grid at different resolutions
layout(matrix(1:2, 1, 2))
plot(MRA_pred$locs_grid[[1]])
plot(MRA_pred$locs_grid[[2]])