make_cov_matC: Make a covariance matrix with covariance function

In nategarton13/sparseRGPs: Fit Sparse Gaussian Processes

Description

Make a covariance matrix with covariance function

Usage

make_cov_matC(x, x_pred, cov_par, cov_fun, delta)

Arguments

x	Matrix of observed data values
x_pred	Potentially an empty matrix. If not empty, this returns the covariance between x and x_pred.
cov_par	Named list of covariance parameters. Need "sigma", "tau", and "l1", ..., "ld" where d is the input dimension
cov_fun	A character string specifying the covariance function. Currently only works with "sqexp".
delta	Scalar value that functions as a fixed nugget used to stabilize matrix inverses and decompositions.

Value

Covariance matrix at the observed data locations if x_pred = matrix(), or the covariances between x and x_pred if x_pred is not an empty matrix.

nategarton13/sparseRGPs documentation built on May 27, 2020, 9:46 a.m.