We’re happy to announce the release of GAUSS 24, with new features for everything from everyday data management to refined statistical modeling. GAUSS 24 features a robust suite of tools designed to elevate your research. With these advancements, GAUSS 24 continues our commitment to helping you conduct insightful analysis and achieve your goals.
The new GAUSS Machine Learning (GML) library offers powerful and efficient machine learning techniques in an accessible and friendly environment. Whether you’re just getting familiar with machine learning or an experienced technician, you’ll be running models in no time with GML.
The preliminary econometric package for Time Series and Panel Data Methods has been updated and functionality has been expanded with over 20 new functions in this release of TSPDLIB 3.0.0. The TSPDLIB 3.0.0 package includes expanded functions for time series and panel data testing both with and without structural breaks and causality testing. It requires a GAUSS 23+ for use.
The new GAUSS 23 is the most practical GAUSS yet! It’s built with the intention to save you time on everyday research tasks like finding, importing, and modeling data. Learn about new features including:
- New FRED and DBnomics data integrations.
- Simplified data loading with intelligent type detection.
- First-class dataframe storage.
- Expanded quantile regressions.
- Kernel density estimation.
- and more …
Introduction The GAUSS TSMT application module provides a comprehensive suite of tools for MLE and state-space estimation, model diagnostics, and forecasting of univariate, multivariate, and nonlinear time series models. The latest Time Series MT (TSMT) 3.1. is now available. If you own TSMT 3.0 the update is available for free. Installation The TSMT update requires [...]
The latest GAUSS 22.1.0 update is available now and is free if you own GAUSS 22. This maintenance release is one of our most extensive with over 40 enhancements, new functions, and new examples, and bug fixes.
GAUSS 22 brings many substantial new features that will save you hours of time and frustration with everyday tasks including:
- Data exploration
- Data cleaning and management
The TSPDLIB 2.1.0 update includes bug fixes, new features, and new examples. It can be easily installed using the GAUSS Package Manager.
Learn why TSPDLIB 2.0 is the easiest and most comprehensive time series and panel data unit root and cointegration testing package on the market. The tspdlib 2.0 package includes expanded functions for time series and panel data testing in the presence of structural breaks. In addition, TSPDLIB 2.0 is easier than ever to use with new implementation of default parameter settings, updated output printing, and automatic date variable detection.
The new dataframes and interactive data management tools in GAUSS 21 will make your work more enjoyable and save you hours of time. Learn more about the latest features including:Tagged in
- New dataframes that handle strings, categories, and dates with ease.
- Interactive data filtering.
- Easy to manage date displays.
- Interactive management of categorial variables.
- Auto-generated code.