elastic.prediction

This function performs prediction from an elastic regression model
with phase-variability

regression

alignment

srvf

Performs alignment, PCA, and modeling of multidimensional and
unidimensional functions using the square-root velocity framework
(Srivastava et al., 2011 <doi:10.48550/arXiv.1103.3817> and Tucker et al., 2014
<DOI:10.1016/j.csda.2012.12.001>). This framework allows for elastic
analysis of functional data through phase and amplitude separation.

J Derek Tucker

fdasrvf

Elastic Functional Data Analysis

J. Derek Tucker

Aymeric Stamm

elastic.prediction function

<dl><dt>f</dt>
<dd>matrix (\(N\) x \(M\)) of \(M\) functions with \(N\) samples</dd>
<dt>time</dt>
<dd>vector of size \(N\) describing the sample points</dd>
<dt>model</dt>
<dd>list describing model from elastic regression methods</dd>
<dt>y</dt>
<dd>responses of test matrix f (default=NULL)</dd>
<dt>smooth_data</dt>
<dd>smooth data using box filter (default = F)</dd>
<dt>sparam</dt>
<dd>number of times to apply box filter (default = 25)</dd></dl>

Arguments

Elastic Prediction from Regression Models — elastic.prediction

<dl>

<dt>f</dt>
<dd>matrix (\(N\) x \(M\)) of \(M\) functions with \(N\) samples</dd>


<dt>time</dt>
<dd>vector of size \(N\) describing the sample points</dd>


<dt>model</dt>
<dd>list describing model from elastic regression methods</dd>


<dt>y</dt>
<dd>responses of test matrix f (default=NULL)</dd>


<dt>smooth_data</dt>
<dd>smooth data using box filter (default = F)</dd>


<dt>sparam</dt>
<dd>number of times to apply box filter (default = 25)</dd>

</dl>

elastic.prediction: Elastic Prediction from Regression Models

Description

Usage

Value

Arguments

References