mra_wendland_2d {BayesMRA} | R Documentation |
Code to construct the mutli-resolution sparse basis function representation for fitting spatial processes
mra_wendland_2d( locs, M = 4, n_coarse_grid = 10, n_padding = 5L, n_neighbors = 68, use_spam = TRUE )
locs |
The location variables in 2 dimensions over which to construct the basis function representation |
M |
The number of resolutions. |
n_coarse_grid |
The number of basis functions in one direction (e.g. |
n_padding |
The number of additional boundary points to add on each boundary. For example, n_padding = 5 will add 5 boundary knots to the both the left and right side of the grid). |
n_neighbors |
The expected number of neighbors for each interior basis function. This determines the basis radius parameter. |
use_spam |
is a boolean flag to determine whether the output is a list of |
A list of objects including the MRA knots locations locs_grid
,
the Wendland basis representation matrix W
at the observed locations,
the basis radius radius
, the numbers of resolutions M
,
the number of expected neighbors in the interior of each grid n_neighbors
,
the number of interior basis functions in one direction n_coarse_grid
,
the number of additional padding basis functions given by n_padding
,
and the setting use_spam
which determines whether the MRA output uses the spam
format.
set.seed(111) locs <- matrix(runif(20), 10, 2) MRA <- mra_wendland_2d(locs, M = 2, n_coarse_grid = 4) ## plot the MRA grid at different resolutions layout(matrix(1:2, 1, 2)) plot(MRA$locs_grid[[1]]) plot(MRA$locs_grid[[2]])