matern_anisotropic3D_alt {GpGp} | R Documentation |
Geometrically anisotropic Matern covariance function (three dimensions, alternate parameterization)
Description
From a matrix of locations and covariance parameters of the form (variance, B11, B12, B13, B22, B23, B33, smoothness, nugget), return the square matrix of all pairwise covariances.
Usage
matern_anisotropic3D_alt(covparms, locs)
Arguments
covparms |
A vector with covariance parameters in the form (variance, B11, B12, B13, B22, B23, B33, 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,]
.
Parameterization
The covariance parameter vector is (variance, B11, B12, B13, B22, B23, B33, smoothness, nugget) where B11, B12, B13, B22, B23, B33, transform the three coordinates as
u_1 = B11[ x_1 + B12 x_2 + (B13 + B12 B23) x_3]
u_2 = B22[ x_2 + B23 x_3]
u_3 = B33[ x_3 ]
NOTE: the u_1 transformation is different from previous versions of this function. NOTE: now (B13,B23) can be interpreted as a drift vector in space over time. Assuming x is transformed to u and y transformed to v, the covariances are
M(x,y) = \sigma^2 2^{1-\nu}/\Gamma(\nu) (|| u - v || )^\nu K_\nu(|| u - v ||)
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
.