multivExpansion

Calculate multivariate basis expansion

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

multivExpansion function

<dl><dt>multiFuns</dt>
<dd>A multivariate functional data object, containing the
multivariate basis functions</dd>
<dt>scores</dt>
<dd>A matrix containing the scores for each observation in each
row. The number of columns must match the number of basis functions.</dd></dl>

Arguments

Calculate multivariate basis expansion — multivExpansion

<dl>

<dt>multiFuns</dt>
<dd>A multivariate functional data object, containing the
multivariate basis functions</dd>


<dt>scores</dt>
<dd>A matrix containing the scores for each observation in each
row. The number of columns must match the number of basis functions.</dd>

</dl>

multivExpansion: Calculate multivariate basis expansion

Description

Usage

Value

Arguments