In this blog, we will explore how to set up and interpret cointegration results using a real-world time series example. We will cover the case with no structural breaks as well as the case with one unknown structural break using tools from the GAUSS tspdlib library.Tagged in
Learn how to create reusable graphics profiles with a few clicks of your mouse.
Learn how to create a simple output table with variable names, parameter estimates and standard errors using sprintf in GAUSS.
Optional input arguments can make your statistical computing more efficient and enjoyable. GAUSS version 20 added a new suite of tools to make it easy for you to add optional input arguments to your GAUSS procedures. This blog lays the foundation to start using optional arguments in your GAUSS programs.
Cointegration is an important tool for modeling the long-run relationships in time series data. If you work with time series data, you will likely find yourself needing to use cointegration at some point. This blog provides an in-depth introduction to cointegration and will cover all the nuts and bolts you need to get started.Tagged in
You’re probably familiar with the basic find-and-replace. However, large projects with many files across several directories, require a more powerful search tool. The GAUSS Source Browser is the powerful search-and-replace tool you need. In this blog, you’ll learn more about using the advanced search-and-replace tools in GAUSS to effectively navigate and edit in projects with multiple files and directories.
The latest Time Series MT (TSMT) 3.1.0 is now available for release. If you own TSMT 3.0 the update is available for free.
Panel data, sometimes referred to as longitudinal data, is data that contains observations about different cross sections across time. Panel data exhibits characteristics of both cross-sectional data and time-series data. This blend of characteristics has given rise to a unique branch of time series modeling made up of methodologies specific to panel data structure. This blog offers a complete guide to those methodologies including the nature of panel data series, types of panel data, and panel data models.
The GAUSS Package Manager, first introduced in version 20, allows you to download, install and uninstall GAUSS packages without leaving GAUSS. It supports the paid GAUSS Application Modules, free GAUSS packages and even allows you to create custom packages and channels. This post will guide you through the basics needed to install and uninstall GAUSS packages.