constraints

Constraints ensure monotonicity of spline coefficients for warping functions 
for use with <code><a href="/link/constrOptim()?package=registr&version=2.1.0" data-mini-rdoc="registr::constrOptim()">constrOptim()</a></code> function.

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

constraints function

<dl><dt>Kh</dt>
<dd>Number of B-spline basis functions used to estimate warping functions h.</dd>
<dt>t_min</dt>
<dd>Minimum value to be evaluated on the time domain.</dd>
<dt>t_max</dt>
<dd>Maximum value to be evaluated on the time domain.</dd>
<dt>warping</dt>
<dd>If <code>nonparametric</code> (default), inverse warping functions are estimated nonparametrically. 
If <code>piecewise_linear2</code> they follow a piecewise linear function with 2 knots.</dd></dl>

Arguments

Julia Wrobel <a href="/link/julia.wrobel%40cuanschutz.edu?package=registr&version=2.1.0" data-mini-rdoc="registr::julia.wrobel@cuanschutz.edu">julia.wrobel@cuanschutz.edu</a>,
Erin McDonnell <a href="/link/eim2117%40cumc.columbia.edu?package=registr&version=2.1.0" data-mini-rdoc="registr::eim2117@cumc.columbia.edu">eim2117@cumc.columbia.edu</a>

Author

Constraints ensure monotonicity of spline coefficients for warping functions 
for use with <code><a href='https://rdrr.io/r/stats/constrOptim.html'>constrOptim()</a></code> function.

Define constraints for optimization of warping functions — constraints

<dl>

<dt>Kh</dt>
<dd>Number of B-spline basis functions used to estimate warping functions h.</dd>


<dt>t_min</dt>
<dd>Minimum value to be evaluated on the time domain.</dd>


<dt>t_max</dt>
<dd>Maximum value to be evaluated on the time domain.</dd>


<dt>warping</dt>
<dd>If <code>nonparametric</code> (default), inverse warping functions are estimated nonparametrically. 
If <code>piecewise_linear2</code> they follow a piecewise linear function with 2 knots.</dd>

</dl>

Julia Wrobel <a href='mailto:julia.wrobel@cuanschutz.edu'>julia.wrobel@cuanschutz.edu</a>,
Erin McDonnell <a href='mailto:eim2117@cumc.columbia.edu'>eim2117@cumc.columbia.edu</a>

constraints: Define constraints for optimization of warping functions

Description

Usage

Value

Arguments

Author