Applications are downloadable libraries that extend the functionality of GAUSS with additional procedures and examples.

TSPDLIB (Time Series Panel Data)

Provides tools for unit root, cointegration, and causality testing in time series and panel data. It includes extensive coverage of testing in the presence of structural breaks.

GML (GAUSS Machine Learning)

Provides tools to model, analyze, and predict data using fundamental machine learning techniques.

TSMT (Time Series MT)

Provides tools for comprehensive treatment of time series models, including model diagnostics, MLE and state-space estimation, and forecasts. Time Series MT also includes tools for managing panel series data and estimating and diagnosing panel series models, including random effects and fixed effects.

SSLIB (State-Space Modeling)

Tools for estimating and evaluating time invariant state space models.