# tseriesEntropy

The R package `tseriesEntropy`

implements an entropy
measure of dependence based on the Bhattacharya-Hellinger-Matusita
distance. It can be used as a (nonlinear)
autocorrelation/crosscorrelation function for continuous and categorical
time series. The package includes tests for serial and cross dependence
and nonlinearity based on it. Some routines have a parallel version that
can be used in a multicore/cluster environment. The package makes use of
S4 classes.

## Authors

## References

Giannerini S., Maasoumi E., Bee Dagum E., (2015), Entropy testing for
nonlinear serial dependence in time series, *Biometrika*,
**102(3)**, 661–675.

Giannerini S, Goracci G. (2023) Entropy-Based Tests for
Complex Dependence in Economic and Financial Time Series with the R
Package tseriesEntropy, *Mathematics*,
**11(3):757**.

Granger C. W. J., Maasoumi E., Racine J., (2004) A dependence metric
for possibly nonlinear processes. *Journal of Time Series
Analysis*, **25(5)**, 649–669.

## Installation

You can install the stable version on CRAN:

`install.packages('tseriesEntropy')`

You can install the development version of tseriesEntropy from GitHub with:

```
# install.packages("devtools")
devtools::install_github("sgiannerini/tseriesEntropy")
```

## License

This package is free and open source software, licensed under
GPL.