scoreplot

Redirects to <code><a href="/link/plot.default?package=MFPCA&version=1.3-10" data-mini-rdoc="MFPCA::plot.default">plot.default</a></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

scoreplot function

<dl><dt>PCAobject</dt>
<dd>A principal component object</dd>
<dt>...</dt>
<dd>Arguments passed from or to other methods</dd></dl>

Arguments

Redirects to <code><a href='https://rdrr.io/r/graphics/plot.default.html'>plot.default</a></code>

Scoreplot Generic — scoreplot

<dl>

<dt>PCAobject</dt>
<dd>A principal component object</dd>


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

</dl>

scoreplot: Scoreplot Generic

Description

Usage

Value

Arguments