CreateModeOfVarPlotLQ2D: Functional Principal Component Analysis mode of variation...

In functionaldata/tDENS: Functional Data Analysis for Density Functions by Transformation to a Hilbert Space

Description

Create 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 variations around the mean: +/- Q sqrt{lambda_k} phi_k for the dark grey area Q = 1, and for the light grey are Q = 2.

Usage

CreateModeOfVarPlotLQ2D(fpcaObj, dSup = NULL, k = 1, domain = "Q",
  alpha = 0, numOfModes = 7, dSupPlot = NULL, ...)

Arguments

fpcaObj	An FPCA class object returned by FPCA().
dSup	The support of the original density used by LQD(relevant only for density domain)
k	The k-th mode of variation to plot (default k = 1)
domain	character defining if we should plot on the Quantile ('Q') or the Density ('D') domain (default: 'Q')
alpha	regularisation parameter
numOfModes	scalar number of principal modes to plot (relevant only for density domain, needs to be an odd number >1.) (default: 7)
dSupPlot	The support of the original density used for plotting (relevant only for density domain)
...	Additional arguments for the 'plot' function.

Examples

library(fdapace)
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)
CreateModeOfVarPlotLQ2D(res)

functionaldata/tDENS documentation built on May 16, 2019, 3:38 p.m.