precision {rSPDE} | R Documentation |
Get the precision matrix of CBrSPDEobj objects
Description
Function to get the precision matrix of a CBrSPDEobj object
Usage
precision(object, ...)
## S3 method for class 'CBrSPDEobj'
precision(
object,
user_nu = NULL,
user_kappa = NULL,
user_sigma = NULL,
user_range = NULL,
user_tau = NULL,
user_m = NULL,
...
)
Arguments
object |
The covariance-based rational SPDE approximation,
computed using |
... |
Currently not used. |
user_nu |
If non-null, update the shape parameter of the covariance function. |
user_kappa |
If non-null, update the range parameter of the covariance function. |
user_sigma |
If non-null, update the standard deviation of the covariance function. |
user_range |
If non-null, update the range parameter of the covariance function. |
user_tau |
If non-null, update the parameter tau. |
user_m |
If non-null, update the order of the rational approximation, which needs to be a positive integer. |
Value
The precision matrix.
See Also
simulate.CBrSPDEobj()
, matern.operators()
Examples
# Compute the covariance-based rational approximation of a
# Gaussian process with a Matern covariance function on R
kappa <- 10
sigma <- 1
nu <- 0.8
range <- 0.2
# create mass and stiffness matrices for a FEM discretization
x <- seq(from = 0, to = 1, length.out = 101)
fem <- rSPDE.fem1d(x)
# compute rational approximation of covariance function at 0.5
tau <- sqrt(gamma(nu) / (sigma^2 * kappa^(2 * nu) *
(4 * pi)^(1 / 2) * gamma(nu + 1 / 2)))
op_cov <- matern.operators(
loc_mesh = x, nu = nu,
range = range, sigma = sigma, d = 1, m = 2,
parameterization = "matern"
)
# Get the precision matrix:
prec_matrix <- precision(op_cov)
[Package rSPDE version 2.3.3 Index]