predict.prcomp_qts

This function predicts the QTS of a new sample from the PCA decomposition of
a previous sample.

An implementation of statistical tools for the analysis
of rotation-valued time series and functional data. It relies on
pre-existing quaternion data structure provided by the 'Eigen' 'C++'
library.

Aymeric Stamm

squat

Statistics for Quaternion Temporal Data

Lise Bellanger

Pierre Drouin

Benjamin Martineau

predict.prcomp_qts function

<dl><dt>object</dt>
<dd>An object of class <code>prcomp_qts</code> as produced by the
<code>prcomp.qts_sample()</code> method.</dd>
<dt>newdata</dt>
<dd>An object of class <code>qts</code> or <code>qts_sample</code> specifying a QTS
or a sample of QTS. The QTS should be evaluated on the same grid as the one
used to fit the PCA model. If the evaluation grids map the same domain but
with different sampling frequenciesa, the QTS will be linearly interpolated
(in the Lie algebra) to the common grid used to fit the PCA model.</dd>
<dt>...</dt>
<dd>Additional arguments. Not used here.</dd></dl>

Arguments

Predict QTS from PCA decomposition — predict.prcomp_qts

<dl>

<dt>object</dt>
<dd>An object of class <code>prcomp_qts</code> as produced by the
<code>prcomp.qts_sample()</code> method.</dd>


<dt>newdata</dt>
<dd>An object of class <code>qts</code> or <code>qts_sample</code> specifying a QTS
or a sample of QTS. The QTS should be evaluated on the same grid as the one
used to fit the PCA model. If the evaluation grids map the same domain but
with different sampling frequenciesa, the QTS will be linearly interpolated
(in the Lie algebra) to the common grid used to fit the PCA model.</dd>


<dt>...</dt>
<dd>Additional arguments. Not used here.</dd>

</dl>

predict.prcomp_qts: Predict QTS from PCA decomposition

Description

Usage

Value

Arguments

Examples