gpr (version 1.1)

covSum: Sum of covariance functions

Description

Provides sum functionality of two covariance functions .

Usage

covSum(covfuncsum , logtheta  = NULL,  x  = NULL, z = NULL, testset.covariances= FALSE)

Arguments

covfuncsum

covfuncsum is a string variable which is consist of two covariance function names seperated by a "," .

logtheta

logtheta is hyperparameter vector variable.

x

Input parameter to define the function over

z

Index number of logtheta vector

testset.covariances

Logic value to decide to compute testset covariances or not.

Value

If z is not null and testset.covariances is TRUE this function calculates test set covariances and if its FALSE the function computes derivative matrix. When covNoise is called without parameters is reports the minimum number of parameters other than logtheta which it can accept. The output of this function is a list consisting variables A and B. B will include testset covariances calculation when testset.covariances is TRUE.

References

Carl Edward Rasmussen and Christopher K. I. Williams.Gaussian Processes for Machine Learning. MIT Press, 2006. ISBN 0-262-18253-X. Carl Edward Rasmussen & Hannes Nickisch. gpml(GAUSSIAN PROCESS REGRESSION AND CLASSIFICATION Toolbox) Matlab Library.

Examples

params= covSum("covSEiso,covNoise")
params