covSum: Sum of covariance functions

In gpr: A Minimalistic package to apply Gaussian Process in R

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.

Author(s)

Afshin Sadeghi

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

Example output

[[1]]
[1] 3

[[2]]
[1] 0

gpr documentation built on May 1, 2019, 8:06 p.m.