gaussian_cor

a list with as many elements as inputs. Each element of the list must be a n times n matrix of differences
between the observation coordinates, with n the number of input coordinates.

an array with the length-scale parameters corresponding to the inputs for which the distance matrices were provided.

thetas

Applies the Gaussian correlation function to a list of distance matrices using corresponding length-scale parameters.

internal

Construction and smart selection of Gaussian process models
with emphasis on treatment of functional inputs. This package
offers: (i) flexible modeling of functional-input regression
problems through the fairly general Gaussian process model; (ii)
built-in dimension reduction for functional inputs; (iii)
heuristic optimization of the structural parameters of the model
(e.g., active inputs, kernel function, type of distance).
Metamodeling background is provided in
Betancourt et al. (2020) <doi:10.1016/j.ress.2020.106870>.
The algorithm for structural parameter optimization is described
in <https://hal.archives-ouvertes.fr/hal-02532713>.

Jose Betancourt

funGp

gaussian_cor: Gaussian correlation function

Description

Usage

Arguments

Value