print.MFPCAfit

A <code>print</code> function for class <code>MFPCAfit</code>.

Calculate a multivariate functional principal component analysis
for data observed on different dimensional domains. The estimation algorithm
relies on univariate basis expansions for each element of the multivariate
functional data (Happ & Greven, 2018) <doi:10.1080/01621459.2016.1273115>.
Multivariate and univariate functional data objects are
represented by S4 classes for this type of data implemented in the package
'funData'. For more details on the general concepts of both packages and a case
study, see Happ-Kurz (2020) <doi:10.18637/jss.v093.i05>.

Clara Happ-Kurz

MFPCA

Multivariate Functional Principal Component Analysis for Data
Observed on Different Dimensional Domains

print.MFPCAfit function

<dl><dt>x</dt>
<dd>An object of class <code>MFPCAfit</code>, usually returned by a
call to MFPCA.</dd>
<dt>...</dt>
<dd>Arguments passed to or from other methods.</dd></dl>

Arguments

Print the results of a Multivariate Functional Principal Component Analysis — print.MFPCAfit

<dl>

<dt>x</dt>
<dd>An object of class <code>MFPCAfit</code>, usually returned by a
call to MFPCA.</dd>


<dt>...</dt>
<dd>Arguments passed to or from other methods.</dd>

</dl>

print.MFPCAfit: Print the results of a Multivariate Functional Principal Component Analysis

Description

Usage

Value

Arguments