rSPDE (version 2.4.0)

precision.rSPDEobj1d: Get the precision matrix of rSPDEobj1d objects

Description

Function to get the precision matrix of a rSPDEobj1d object

Usage

# S3 method for rSPDEobj1d
precision(
  object,
  loc = NULL,
  nu = NULL,
  kappa = NULL,
  sigma = NULL,
  range = NULL,
  tau = NULL,
  m = NULL,
  ordering = c("field", "location"),
  ldl = FALSE,
  ...
)

Value

A list containing the precision matrix Q of the process and its derivatives if they exist, and a matrix A that extracts the elements corresponding to the process. If ldl=TRUE, the LDL factorization is returned instead of Q. If the locations are not ordered, the precision matrix is given for the ordered locations, but the A matrix returns to the original order.

Arguments

object

The covariance-based rational SPDE approximation, computed using matern.rational()

loc

If non-null, update the locations where to evaluate the model.

nu

If non-null, update the shape parameter of the covariance function.

kappa

If non-null, update the range parameter of the covariance function.

sigma

If non-null, update the standard deviation of the covariance function.

range

If non-null, update the range parameter of the covariance function.

tau

If non-null, update the parameter tau.

m

If non-null, update the order of the rational approximation, which needs to be a positive integer.

ordering

Return the matrices ordered by field or by location?

ldl

Directly build the LDL factorization of the precision matrix?

...

Currently not used.

See Also

simulate.rSPDEobj1d(), matern.rational()

Examples

# Compute the covariance-based rational approximation of a
# Gaussian process with a Matern covariance function on R
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)

op_cov <- matern.rational(
  loc = x, nu = nu,
  range = range, sigma = sigma, m = 2,
  parameterization = "matern"
)

# Get the precision matrix:
prec_matrix <- precision(op_cov)