cov.noisy.SE.d: Partial derivatives of the noisy SE covariance function

In JimSkinner/spca: Structured PCA

Description

Partial derivatives of the noisy SE covariance function

Usage

cov.noisy.SE.d(X, X2, beta, D = NA, ...)

Arguments

X	Matrix of data
X2	(optional) second matrix of data; if omitted, X is used.
beta	Hyperparameters; beta[1] is the log signal variance, beta[2] is the log length scale, beta[3] is the variance of the noise.

JimSkinner/spca documentation built on May 7, 2019, 10:52 a.m.