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Models
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This section documents the available models. For quick iteration during development, the modules containing the models
can be executed directly to test the models.

LSTM
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This model is based on the Long Short Term Memory deep learning model, and is implemented using Keras.

Arima
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Simple ARIMA model implemented using the PyFlux library.

GAS
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Simple GAS model implemented using the PyFlux library.

Vector auto regression
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The VAR model is implemented following the tutorial on PyFlux.

R_forecast
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This model uses the R library `forecast <https://cran.r-project.org/web/packages/forecast/index.html>`. So in order to
run it you must have R with the forecast package installed.

Currently the model adjusted to the curves is a simple arima, but more sophisticated models are available in R which can be tried.

Also this model can serve as a template for the implementation of other R based predictive models, using rpy2 as a
bridge between Python and R.