qwdap.plsr

Partial least squares regression. This is a linear regression method used to
establish the linear relationship between the original time series and the modes
generated by quantum walks.

The modeling and prediction of graph-associated time series(GATS) based on continuous time quantum walk. This software is mainly used for feature extraction, modeling, prediction and result evaluation of GATS, including continuous time quantum walk simulation, feature selection, regression analysis, time series prediction, and series fit calculation. A paper is attached to the package for reference.

Binghuang Pan

QWDAP

Quantum Walk-Based Data Analysis and Prediction

Zhaoyuan Yu

Xu Hu

Yuhao Teng

qwdap.plsr function

<dl><dt>in_data</dt>
<dd>a 'QWMS' object, which includes the target series and the
selected modes which can be obtained from modes selection.</dd>
<dt>data_range</dt>
<dd>the range of the train samples.</dd>
<dt>plotting</dt>
<dd>whether to plot.</dd></dl>

Arguments

Partial Least Squares Regression — qwdap.plsr

<dl>

<dt>in_data</dt>
<dd>a 'QWMS' object, which includes the target series and the
selected modes which can be obtained from modes selection.</dd>


<dt>data_range</dt>
<dd>the range of the train samples.</dd>


<dt>plotting</dt>
<dd>whether to plot.</dd>

</dl>

qwdap.plsr: Partial Least Squares Regression

Description

Usage

Value

Arguments

Examples