par.mFPCA: Setting mixed functional principal component analysis (mFPCA)...

In funcharts: Functional Control Charts

Setting mixed functional principal component analysis (mFPCA) defaults

Description

This is an internal function of package FRTM which allows controlling the parameters used in the mFPCA in the FRTM method.

Usage

par.mFPCA(perc_pca = 0.9, perc_basis_x_pca = 1, perc_basis_h = 0.2)

Arguments

perc_pca	Percentage of the total variability used to select the number L of principal components.
perc_basis_x_pca	Multiplied by the maximum number of basis of the registered functions for each time point in \mathcal{D}_{Y}, it is the number of basis functions of the registered functions in the mFPCA.
perc_basis_h	Multiplied by the mean number of basis of the warping functions for each time point in \mathcal{D}_{Y}, it is the number of basis functions of the warping functions in the mFPCA.

See Also

FRTM_PhaseI

Examples

library(funcharts)
par.mFPCA()

funcharts documentation built on April 3, 2025, 7:47 p.m.