cov.noisy.SE: Noisy SE covariance function

Description Usage Arguments

View source: R/covariance-functions.R

Description

The sum of the Squared Exponential and the independent covariance functions. Interpreted as the smooth SE covariance function plus iid noise. This is implemented as the sum of two covariance functions, with the first two elements of beta being sent to the SE covariance function, and the last element being sent to the independent covariance function.

Usage

1
cov.noisy.SE(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 Aug. 19, 2018, 7 a.m.