Time Series MT 2.1
Times Series MT provides for comprehensive treatment of time series models, including model diagnostics, MLE estimation, and forecasts. Time Series MT tools covers panel series models including random effects and fixed effects, while allowing for unbalanced panels.
- New Estimate models with multiple structural breaks
- New Estimate Threshold Autoregressive models
- New Rolling and recursive OLS estimation
- Least Squares Dummy Variable model for multivariate data with bias correction of the parameters.
- Hamilton’s Regime-Switching Regression model
- Seasonal VARMAX models
- Time Series Cross-Sectional Regression models
- Weighted Maximum Likelihood
- ARIMA model estimation and forecasts
- Exact full information maximum likelihood estimation of VARMAX, VARMA, ARIMAX, and ECM models.
- Standard time series diagnostic tests including unit root tests, cointegration tests, and lag selection tests.
Estimate and the autocorrelations, autocovariances, and coefficients of a regression model with autoregressive errors of any specified order.
Markov-Switching model. Click here.
Provide a GAUSS procedure for estimation of the parameters of the Markov switching regression model.
Platform: Windows, Mac and Linux.
Requirements: GAUSS/GAUSS Light version 13.1 or higher.