Description Usage Arguments Value Functions Parameterization
From a matrix of locations and covariance parameters of the form (variance, range_1, ..., range_d, nugget), return the square matrix of all pairwise covariances.
1 2 3 | exponential_scaledim(covparms, locs)
d_exponential_scaledim(covparms, locs)
|
covparms |
A vector with covariance parameters in the form (variance, range_1, ..., range_d, nugget) |
locs |
A matrix with |
A matrix with n
rows and n
columns, with the i,j entry
containing the covariance between observations at locs[i,]
and
locs[j,]
.
d_exponential_scaledim
: Derivatives with respect to parameters
The covariance parameter vector is (variance, range_1, ..., range_d, nugget). The covariance function is parameterized as
M(x,y) = σ^2 exp( - || D^{-1}(x - y) || )
where D is a diagonal matrix with (range_1, ..., range_d) on the diagonals. The nugget value σ^2 τ^2 is added to the diagonal of the covariance matrix. NOTE: the nugget is σ^2 τ^2 , not τ^2 .
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