exponential_anisotropic3D_alt: Geometrically anisotropic exponential covariance function...

In GpGp: Fast Gaussian Process Computation Using Vecchia's Approximation

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

exponential_anisotropic3D_alt(covparms, locs)

d_exponential_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 n rows and 3 columns. Each row of locs is a point in R^3.

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_exponential_anisotropic3D_alt: Derivatives of anisotropic Matern covariance

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GpGp documentation built on June 10, 2021, 1:07 a.m.