Welcome to Arauto’s documentation!


Arauto is an open-source and interactive tool for quick prototyping and experimentation of time series models. You can use it to build mixed autoregressive moving average models (AR, MA, ARMA, ARIMA, SARIMA, ARIMAX, SARIMAX).

Arauto offers an intuitive experience, so you can focus on the results of your model. Among other things, it supports exogenous variables and let you customize the whole process, from choosing a specific transformation function to test different parameters. Check it out the main features of Arauto:

  • Support to exogenous regressors (independent variables);
  • Seasonal decompose that let’s you know the Trend, Seasonality and Resid of your data;
  • Stationarity Test using Augmented Dickey-Fuller test;
  • Customization of data transforming for stationarity: you can use from first difference to seasonal log to transform your data;
  • ACF (Autocorrelation function) and PACF (Parcial correlation function) for terms estimation;
  • Customize ARIMA terms or let Arauto choose the best for you based on your data;
  • Grid search feature for parameters tuning;
  • Code generation: at the end of the process, Arauto returns the code used to perform each step.