README.Rmd

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# fastEDM <img src="man/figures/logo.png" align="right" height="200" alt="logo" />

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The `fastEDM` R package implements a series of  _Empirical Dynamic Modeling_ tools that can be used for _causal analysis of time series_ data.

Key features of the package:

- powered by a fast multi-threaded _C++ backend_,
- able to process panel data, a.k.a. _multispatial EDM_,
- able to handle _missing data_ using new `dt` algorithms or by dropping points.


## Installation

You can install the development version of fastEDM from [GitHub](https://github.com/EDM-Developers/fastEDM-r/) with:

``` r
# install.packages("devtools")
devtools::install_github("EDM-Developers/fastEDM-r")
```

## Example: Chicago crime levels and temperature

This example, looking at the causal links between Chicago's temperature and crime rates, is described in full in our [paper](https://jinjingli.github.io/edm/edm-wp.pdf):

```{r example, file='man/chicago-easy-edm-example.R'}
```

## Stata & Python Packages

This package is an R port of our [EDM Stata package](https://edm-developers.github.io/edm-stata/).
Similarly, we are creating a [fastEDM Python package](https://edm-developers.github.io/fastEDM-python/).
As the packages share the same underlying C++ code, their behaviour will be identical.
If you plan to adjust some of the various low-level EDM parameters, check out the documentation of the Stata package for more details on their options and behaviours.