gaussianProcess: Create a gaussianProcess object with a given mean function...

Description Usage Arguments Value

View source: R/gaussianProcess.R

Description

Create a gaussianProcess object with a given mean function and covariance kernel, and data

Usage

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gaussianProcess(X, y, meanFunc = zeroFunction, kernel = rbf,
  hyper.params = NULL, noise.var = 1, order = 5/2, verbose = 0)

Arguments

X

An n x d matrix of covariates for observed data

y

An n dimensional vector of outputs for observed data

meanFunc

The mean function of the process, defaults to 0

kernel

The covariance kernel of the process, defaults to rbf

hyper.params

The hyper parameters for the kernel (c(amplitude, scales)), if NULL then optimize them using the log likelihood

noise.var

The variance of the noise around the function

order

The order of the kernel, defaults to 5/2

verbose

Level of information printed out, defaults to 0

Value

A gaussianProcess with these options


ebenmichael/gaussianProcess documentation built on May 13, 2017, 10:58 a.m.