rspde.matern.precision.opt | R Documentation |
rspde.matern.precision
is used for computing the
optimized version of the precision matrix of the
covariance-based rational SPDE approximation of a stationary Gaussian random
fields on R^d
with a Matern covariance function
C(h) = \frac{\sigma^2}{2^{\nu-1}\Gamma(\nu)}(\kappa h)^\nu
K_\nu(\kappa h).
rspde.matern.precision.opt(
kappa,
nu,
tau,
rspde.order,
dim,
fem_matrices,
graph = NULL,
sharp,
type_rational_approx
)
kappa |
Range parameter of the covariance function. |
nu |
Shape parameter of the covariance function. |
tau |
Scale parameter of the covariance function. |
rspde.order |
The order of the rational approximation |
dim |
The dimension of the domain |
fem_matrices |
A list containing the FEM-related matrices. The list should contain elements C, G, G_2, G_3, etc. |
graph |
The sparsity graph of the matrices. If NULL, only a vector of the elements will be returned, if non-NULL, a sparse matrix will be returned. |
sharp |
The sparsity graph should have the correct sparsity (costs more to perform a sparsity analysis) or an upper bound for the sparsity? |
type_rational_approx |
Which type of rational approximation should be used? The current types are "chebfun", "brasil" or "chebfunLB". |
The precision matrix
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