Update parameters of rSPDEobj objects

Function to change the parameters of a rSPDEobj object

Usage

# S3 method for class 'rSPDEobj'
update(
  object,
  nu = NULL,
  alpha = NULL,
  kappa = NULL,
  sigma = NULL,
  range = NULL,
  tau = NULL,
  theta = NULL,
  m = NULL,
  mesh = NULL,
  loc_mesh = NULL,
  graph = NULL,
  range_mesh = NULL,
  parameterization = NULL,
  ...
)

Arguments

object: The operator-based rational SPDE approximation, computed using matern.operators() with type="operator"
nu: If non-null, update the shape parameter of the covariance function.
alpha: If non-null, update the fractional order.
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.
theta: If non-null, update the parameter theta, that connects tau and kappa to the model matrices.
m: If non-null, update the order of the rational approximation, which needs to be a positive integer.
mesh: An optional inla mesh. Replaces d, C and G.
loc_mesh: The mesh locations used to construct the matrices C and G. This option should be provided if one wants to use the rspde_lme() function and will not provide neither graph nor mesh. Only works for 1d data. Does not work for metric graphs. For metric graphs you should supply the graph using the graph argument.
graph: An optional metric_graph object. Replaces d, C and G.
range_mesh: The range of the mesh. Will be used to provide starting values for the parameters. Will be used if mesh and graph are NULL, and if one of the parameters (kappa or tau for spde parameterization, or sigma or range for matern parameterization) are not provided.
parameterization: If non-null, update the parameterization. Only works for stationary models.
...: Currently not used.

Value

It returns an object of class "rSPDEobj. This object contains the same quantities listed in the output of matern.operators().

Examples

# Compute the operator-based rational approximation of a
# Gaussian process with a Matern covariance function on R
kappa <- 10
sigma <- 1
nu <- 0.8
range <- sqrt(8 * nu) / kappa

# 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
op <- matern.operators(
  loc_mesh = x, nu = nu,
  range = range, sigma = sigma, d = 1, m = 2, type = "operator",
  parameterization = "matern"
)
op
#> Type of approximation:  Matern approximation 
#> Parameterization:  matern 
#> Parameters of covariance function: range =  0.2529822 , sigma =  1 , nu =  0.8 
#> Order or rational approximation:  2 
#> Size of discrete operators:  101  x  101 
#> Stationary Model

# Update the range parameter of the model:
op <- update(op, kappa = 20)
op
#> Type of approximation:  Matern approximation 
#> Parameterization:  matern 
#> Parameters of covariance function: range =  0.2529822 , sigma =  1 , nu =  0.8 
#> Order or rational approximation:  2 
#> Size of discrete operators:  101  x  101 
#> Stationary Model

Usage

Arguments

Value

See also

Examples