predict.lpcr

This function performs prediction from an elastic logistic fPCR 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

predict.lpcr function

<dl><dt>object</dt>
<dd>Object of class inheriting from "elastic.pcr.regression"</dd>
<dt>newdata</dt>
<dd>An optional matrix in which to look for variables with which to predict. If omitted, the fitted values are used.</dd>
<dt>y</dt>
<dd>An optional vector of labels to calculate PC. If omitted, PC is NULL</dd>
<dt>...</dt>
<dd>additional arguments affecting the predictions produced</dd></dl>

Arguments

Elastic Prediction for functional logistic PCR Model — predict.lpcr

<dl>

<dt>object</dt>
<dd>Object of class inheriting from "elastic.pcr.regression"</dd>


<dt>newdata</dt>
<dd>An optional matrix in which to look for variables with which to predict. If omitted, the fitted values are used.</dd>


<dt>y</dt>
<dd>An optional vector of labels to calculate PC. If omitted, PC is NULL</dd>


<dt>...</dt>
<dd>additional arguments affecting the predictions produced</dd>

</dl>

predict.lpcr: Elastic Prediction for functional logistic PCR Model

Description

Usage

Value

Arguments

References