crossprods_regular

Compute the crossproduct in a fast way for mostly regular grids
(index values are mostly *not* unique).
Only used internally in <code>cov_hall()</code>.

A method for performing joint registration and functional principal
component analysis for curves (functional data) that are generated from exponential family distributions. This
mainly implements the algorithms described in 'Wrobel et al. (2019)' <doi:10.1111/biom.12963> and further adapts them to potentially
incomplete curves where (some) curves are not observed from the beginning and/or until the end of the common domain. Curve registration
can be used to better understand patterns in functional data by separating curves into phase and amplitude variability.
This software handles both binary and continuous functional data, and is
especially applicable in accelerometry and wearable technology.

Julia Wrobel

registr

Curve Registration for Exponential Family Functional Data

Alexander Bauer

Erin McDonnell

Fabian Scheipl

Jeff Goldsmith

crossprods_regular function

<dl><dt>Y</dt>
<dd>Dataframe with the centered observations.
Should have values id, centered, index.</dd></dl>

Arguments

Crossproduct computation for mostly regular grids — crossprods_regular

<dl>

<dt>Y</dt>
<dd>Dataframe with the centered observations.
Should have values id, centered, index.</dd>

</dl>

crossprods_regular: Crossproduct computation for mostly regular grids

Description

Usage

Arguments