df.test

Models for non-linear time series analysis and causality detection. The main functionalities of this package consist of an implementation of the classical causality test (C.W.J.Granger 1980) <doi:10.1016/0165-1889(80)90069-X>, and a non-linear version of it based on feed-forward neural networks. This package contains also an implementation of the Transfer Entropy <doi:10.1103/PhysRevLett.85.461>, and the continuous Transfer Entropy using an approximation based on the k-nearest neighbors <doi:10.1103/PhysRevE.69.066138>. There are also some other useful tools, like the VARNN (Vector Auto-Regressive Neural Network) prediction model, the Augmented test of stationarity, and the discrete and continuous entropy and mutual information.

Youssef Hmamouche

NlinTS

Models for Non Linear Causality Detection in Time Series

df.test function

<dl><dt>ts</dt>
<dd>Numerical dataframe.</dd>
<dt>lag</dt>
<dd>The lag parameter.</dd></dl>

Arguments

Augmented Dickey_Fuller test — df.test

<dl>

<dt>ts</dt>
<dd>Numerical dataframe.</dd>


<dt>lag</dt>
<dd>The lag parameter.</dd>

</dl>

df.test: Augmented Dickey_Fuller test

Description

Usage

Value

Arguments

Details

References

Examples