fpca_gauss_argPreparation

Internal main preparation function for fpca_gauss

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

fpca_gauss_argPreparation function

<dl><dt>Y, time, t_min, t_max</dt>
<dd>Internal objects created in <code>fpca_gauss</code>.</dd>
<dt>Kt</dt>
<dd>Number of B-spline basis functions used to estimate mean functions
and functional principal components. Default is 8. If <code>npc_varExplained</code>
is used, <code>Kt</code> is set to 20.</dd>
<dt>periodic</dt>
<dd>If TRUE, uses periodic b-spline basis functions. Default is FALSE.</dd>
<dt>seed</dt>
<dd>Set seed for reproducibility. Defaults to 1988.</dd>
<dt>subsample</dt>
<dd>if the number of rows of the data is greater than 
10 million rows, the `id` values are subsampled to get the mean coefficients.</dd>
<dt>verbose</dt>
<dd>Can be set to integers between 0 and 4 to control the level of
detail of the printed diagnostic messages. Higher numbers lead to more detailed
messages. Defaults to 1.</dd></dl>

Arguments

Internal main preparation function for fpca_gauss — fpca_gauss_argPreparation

<dl>

<dt>Y, time, t_min, t_max</dt>
<dd>Internal objects created in <code>fpca_gauss</code>.</dd>


<dt>Kt</dt>
<dd>Number of B-spline basis functions used to estimate mean functions
and functional principal components. Default is 8. If <code>npc_varExplained</code>
is used, <code>Kt</code> is set to 20.</dd>


<dt>periodic</dt>
<dd>If TRUE, uses periodic b-spline basis functions. Default is FALSE.</dd>


<dt>seed</dt>
<dd>Set seed for reproducibility. Defaults to 1988.</dd>


<dt>subsample</dt>
<dd>if the number of rows of the data is greater than 
10 million rows, the `id` values are subsampled to get the mean coefficients.</dd>


<dt>verbose</dt>
<dd>Can be set to integers between 0 and 4 to control the level of
detail of the printed diagnostic messages. Higher numbers lead to more detailed
messages. Defaults to 1.</dd>

</dl>

fpca_gauss_argPreparation: Internal main preparation function for fpca_gauss

Description

Usage

Value

Arguments