local_basis | R Documentation |
Construct a set of local basis functions based on pre-specified location and scale parameters.
local_basis(
manifold = sphere(),
loc = matrix(c(1, 0), nrow = 1),
scale = 1,
type = c("bisquare", "Gaussian", "exp", "Matern32"),
res = 1,
regular = FALSE
)
radial_basis(
manifold = sphere(),
loc = matrix(c(1, 0), nrow = 1),
scale = 1,
type = c("bisquare", "Gaussian", "exp", "Matern32")
)
manifold |
object of class |
loc |
a matrix of size |
scale |
vector of length |
type |
either |
res |
vector of length |
regular |
logical indicating if the basis functions (of each resolution) are in a regular grid |
This functions lays out local basis functions in a domain of interest based on pre-specified location and scale parameters. If type
is “bisquare”, then
\phi(u) = \left(1- \left(\frac{\| u \|}{R}\right)^2\right)^2 I(\|u\| < R),
and scale
is given by R
, the range of support of the bisquare function. If type
is “Gaussian”, then
\phi(u) = \exp\left(-\frac{\|u \|^2}{2\sigma^2}\right),
and scale
is given by \sigma
, the standard deviation. If type
is “exp”, then
\phi(u) = \exp\left(-\frac{\|u\|}{ \tau}\right),
and scale
is given by \tau
, the e-folding length. If type
is “Matern32”, then
\phi(u) = \left(1 + \frac{\sqrt{3}\|u\|}{\kappa}\right)\exp\left(-\frac{\sqrt{3}\| u \|}{\kappa}\right),
and scale
is given by \kappa
, the function's scale.
auto_basis
for constructing basis functions automatically, and show_basis
for visualising basis functions.
library(ggplot2)
G <- local_basis(manifold = real_line(),
loc=matrix(1:10,10,1),
scale=rep(2,10),
type="bisquare")
## Not run: show_basis(G)
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