plot.gpfr: Plot GPFR model for either training or prediction

plot.gpfrR Documentation

Plot GPFR model for either training or prediction

Description

Plot GPFR model for either training or prediction

Usage

## S3 method for class 'gpfr'
plot(
  x,
  type = c("raw", "meanFunction", "fitted", "prediction"),
  ylab = "y",
  xlab = "t",
  ylim = NULL,
  realisations = NULL,
  alpha = 0.05,
  colourTrain = 2,
  colourNew = 4,
  mar = c(4.5, 5.1, 2.2, 0.8),
  oma = c(0, 0, 1, 0),
  cex.lab = 1.5,
  cex.axis = 1,
  cex.main = 1.5,
  ...
)

Arguments

x

Plot GPFR for training or prediction from a given object of 'gpfr' class.

type

Required type of plots. Options are: 'raw', 'meanFunction', 'fitted' and 'prediction'.

ylab

Title for the y axis.

xlab

Title for the x axis.

ylim

Graphical parameter. If NULL (default), it is chosen automatically.

realisations

Index vector identifying which training realisations should be plotted. If NULL (default), all training realisations are plotted. For predictions, 'realisations' should be '0' if no training realisation is to be plotted.

alpha

Significance level used for 'fitted' or 'prediction'. Default is 0.05.

colourTrain

Colour for training realisations when 'type' is set to 'prediction' and 'realisations' is positive.

colourNew

Colour for predictive mean for the new curve when 'type' is set to 'prediction'.

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().

...

Other graphical parameters passed to plot().

Value

A plot.

Examples

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

GPFDA documentation built on May 7, 2022, 5:06 p.m.