matern_isotropic {GpGp} | R Documentation |
Isotropic Matern covariance function
Description
From a matrix of locations and covariance parameters of the form (variance, range, smoothness, nugget), return the square matrix of all pairwise covariances.
Usage
matern_isotropic(covparms, locs)
d_matern_isotropic(covparms, locs)
Arguments
covparms |
A vector with covariance parameters in the form (variance, range, smoothness, nugget) |
locs |
A matrix with |
Value
A matrix with n
rows and n
columns, with the i,j entry
containing the covariance between observations at locs[i,]
and
locs[j,]
.
Functions
-
d_matern_isotropic()
: Derivatives of isotropic Matern covariance
Parameterization
The covariance parameter vector is (variance, range, smoothness, nugget)
= (\sigma^2,\alpha,\nu,\tau^2)
, and the covariance function is parameterized
as
M(x,y) = \sigma^2 2^{1-\nu}/\Gamma(\nu) (|| x - y ||/\alpha )^\nu K_\nu(|| x - y ||/\alpha )
The nugget value \sigma^2 \tau^2
is added to the diagonal of the covariance matrix.
NOTE: the nugget is \sigma^2 \tau^2
, not \tau^2
.