GPFDA (version 3.1.3)

plotmgpCovFun: Plot auto- or cross-covariance function of a multivariate Gaussian process

Description

Plot auto- or cross-covariance function of a multivariate Gaussian process

Usage

plotmgpCovFun(
  type = "Cov",
  output,
  outputp,
  Data,
  hp,
  idx,
  ylim = NULL,
  xlim = NULL,
  mar = c(4.5, 5.1, 2.2, 0.8),
  oma = c(0, 0, 0, 0),
  cex.lab = 1.5,
  cex.axis = 1,
  cex.main = 1.5
)

Value

A plot

Arguments

type

Logical. It can be either 'Cov' (for covariance function) or 'Cor' (for corresponding correlation function).

output

Integer identifying one element of the multivariate process.

outputp

Integer identifying one element of the multivariate process. If 'output' and 'outputp' are the same, the auto-covariance function will be plotted. Otherwise, the cross-covariance function between 'output' and 'outputp' will be plotted.

Data

List of two elements: 'input' and 'response'. The element 'input' is a list of N vectors, where each vector represents the input covariate values for a particular output. The element 'response' is the corresponding list of N matrices (if there are multiple realisations) or vectors (for a single realisation) representing the response variables.

hp

Vector of hyperparameters

idx

Index vector identifying to which output the elements of concatenated vectors correspond to.

ylim

Graphical parameter

xlim

Graphical parameter

mar

Graphical parameter passed to par().

oma

Graphical parameter passed to par().

cex.lab

Graphical parameter passed to par().

cex.axis

Graphical parameter passed to par().

cex.main

Graphical parameter passed to par().

Examples

## See examples in vignette:
# vignette("mgpr", package = "GPFDA")