Overview
Time Series MT (TSMT) 4.0 is a comprehensive GAUSS package for time-series modeling, diagnostics, forecasting, maximum-likelihood estimation, state-space estimation, and panel-series analysis.
TSMT 4.0 is a major upgrade with more than 40 new features, enhancements, and improvements designed to make advanced time-series analysis more accessible and productive.
What’s new in TSMT 4.0
- Structural VAR modeling: Estimate reduced-form VAR parameters, impulse response functions, and forecast error variance decompositions with built-in Cholesky, sign-restriction, and long-run identification strategies.
- Improved SARIMA modeling: More stable estimation, robust covariance estimates, stationarity and invertibility enforcement, smarter defaults, and support for special cases such as white noise and random walks.
- Clearer diagnostics and reporting: Cleaner output, expanded diagnostics, and summaries that make model evaluation and comparison easier.
- GAUSS dataframe integration: Automatic handling of variable names and time spans, less manual data preparation, and more readable output.
Related learning
- Announcing Time Series MT 4.0
- Sign-Restricted SVAR in GAUSS
- Introduction to Time Series Data and Analysis
Selected examples
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The documentation includes current commands, detailed capabilities, installation guidance, and examples.