CreateModeOfVarPlot: Functional Principal Component Analysis: Mode of variation...

In fdapace: Functional Data Analysis and Empirical Dynamics

Functional Principal Component Analysis: Mode of variation plot

Description

Creates the k-th mode of variation plot around the mean. The red-line is the functional mean, the grey shaded areas show the range of variation around the mean: \pm Q \sqrt{\lambda_k} \phi_k for the dark grey area Q = 1, and for the light grey are Q = 2. In the case of 'rainbowPlot' the blue edge corresponds to Q = -3, the green edge to Q = +3 and the red-line to Q = 0 (the mean).

Usage

CreateModeOfVarPlot(
  fpcaObj,
  k = 1,
  rainbowPlot = FALSE,
  colSpectrum = NULL,
  ...
)

Arguments

fpcaObj	An FPCA class object returned by FPCA().
k	The k-th mode of variation to plot (default k = 1)
rainbowPlot	Indicator to create a rainbow-plot instead of a shaded plot (default: FALSE)
colSpectrum	Character vector to be use as input in the 'colorRampPalette' function defining the outliers colours (default: c("blue","red", "green"), relevant only for rainbowPlot=TRUE)
...	Additional arguments for the plot function.

Examples

set.seed(1)
n <- 20
pts <- seq(0, 1, by=0.05)
sampWiener <- Wiener(n, pts)
sampWiener <- Sparsify(sampWiener, pts, 10)
res <- FPCA(sampWiener$Ly, sampWiener$Lt, 
            list(dataType='Sparse', error=FALSE, kernel='epan', verbose=TRUE))
CreateModeOfVarPlot(res)

fdapace documentation built on July 3, 2024, 5:08 p.m.