GAUSS procedures are user-defined functions that allow you to combine a sequence of commands to perform desired tasks. In this blog, you will learn the fundamentals of creating and using procedures in GAUSS.
Often times we need to mix multiple graph types in order to create a plot which most effectively tells the story of our data. In this post, we will create a plot of the Phillips Curve in the United States over two separate time periods. We will show how to add scatter points and lines as well as data series’ of different lengths to a single plot. However, our main focus will be showing you how to control the styling of all aspects of the plot in these cases.
GAUSS packages provide access to powerful tools for performing data analysis. This guide covers all you need to know to get the most from GAUSS packages including:
- What is a GAUSS package
- Where to find GAUSS packages
- What is included in GAUSS packages
- How to use GAUSS packages
Learn how to work with matrices, the building block of the GAUSS programming language, in this third video in our GAUSS Basics series. Today we will explore how to:Tagged in
- Create matrices.
- Find their size.
- Access specific elements with indexing.
- Grow matrices with matrix concatenation.
This second video in our new GAUSS basics series shows you how to create and run a GAUSS program.Tagged in
This is the first video in our new GAUSS Basics series. This series is designed to teach you everything you need to know to be productive with GAUSS. This video covers interactive commands and is designed to be your first step in GAUSS!Tagged in
The GAUSS interface includes a number of often overlooked hotkeys and shortcuts. These features can help make programming more efficient and navigation seamless. In this blog I highlight my top five GAUSS hotkeys:Tagged in
- Quickly view data symbols using
- Open floating command reference pages using
- Toggle block comments on and off using
- Go to procedure definitions using
- Delete lines using
In this blog, we explore data path best practices for making GAUSS code more portable and replicable. Using variables and predefined GAUSS path definitions, we show how to simplify code and easily customize data loading.Tagged in