rSPDE (version 2.5.1)

update.rSPDEobj1d: Update parameters of rSPDEobj1d objects

Description

Function to change the parameters of a rSPDEobj1d object

Usage

# S3 method for rSPDEobj1d
update(
  object,
  nu = NULL,
  alpha = NULL,
  kappa = NULL,
  tau = NULL,
  sigma = NULL,
  range = NULL,
  theta = NULL,
  m = NULL,
  loc = NULL,
  graph = NULL,
  parameterization = NULL,
  type_rational_approximation = object$type_rational_approximation,
  ...
)

Value

It returns an object of class "rSPDEobj1d". This object contains the same quantities listed in the output of matern.rational().

Arguments

object

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

nu

If non-null, update the shape parameter of the covariance function. Will be used if parameterization is 'matern'.

alpha

If non-null, update the fractional SPDE order parameter. Will be used if parameterization is 'spde'.

kappa

If non-null, update the parameter kappa of the SPDE. Will be used if parameterization is 'spde'.

tau

If non-null, update the parameter tau of the SPDE. Will be used if parameterization is 'spde'.

sigma

If non-null, update the standard deviation of the covariance function. Will be used if parameterization is 'matern'.

range

If non-null, update the range parameter of the covariance function. Will be used if parameterization is 'matern'.

theta

For non-stationary models. If non-null, update the vector of parameters.

m

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

loc

The locations of interest for evaluating the model.

graph

An optional metric_graph object.

parameterization

If non-null, update the parameterization.

type_rational_approximation

Which type of rational approximation should be used? The current types are "chebfun", "brasil" or "chebfunLB".

...

Currently not used.

See Also

simulate.rSPDEobj1d(), matern.rational()

Examples

s <- seq(from = 0, to = 1, length.out = 101)
kappa <- 20
sigma <- 2
nu <- 0.8
r <- sqrt(8*nu)/kappa #range parameter
op_cov <- matern.rational(loc = s, nu = nu, range = r, sigma = sigma, m = 2, 
parameterization = "matern")
cov1 <- op_cov$covariance(ind = 1)
op_cov <- update(op_cov, range = 0.2)
cov2 <- op_cov$covariance(ind = 1)
plot(s, cov1, type = "l")
lines(s, cov2, col = 2)