R: Models for Non Linear Causality Detection in Time Series

# Models for Non Linear Causality Detection in Time Series

## Documentation for package ‘NlinTS’ version 1.4.5

- DESCRIPTION file.

## Help Pages

NlinTS-package | Models for non-linear causality detection in time series.
causality.test | The Granger causality test
df.test | Augmented Dickey_Fuller test
entropy_cont | Continuous entropy
entropy_disc | Discrete Entropy
mi_cont | Continuous Mutual Information
mi_disc | Discrete multivariate Mutual Information
mi_disc_bi | Discrete bivariate Mutual Information
NlinTS | Models for non-linear causality detection in time series.
nlin_causality.test | A non linear Granger causality test
te_cont | Continuous Transfer Entropy
te_disc | Discrete Transfer Entropy
varmlp | Artificial Neural Network VAR (Vector Auto-Regressive) model using a MultiLayer Perceptron, with the sigmoid activation function. The optimization algorithm is based on the stochastic gradient descent.