GAUSS Basics 2: Running a program
This second video in our new GAUSS basics series shows you how to create and run a GAUSS program.
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GAUSS Basics: Interactive commands
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!
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Panel data, structural breaks and unit root testing
In this blog, we extend our analysis of unit root testing with structural breaks to panel data. Using panel data unit roots tests found in the GAUSS tspdlib we consider if a panel of international current account balances collectively shows unit root behavior.
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Unit Root Tests with Structural Breaks
In this blog, we examine the issue of identifying unit roots in the presence of structural breaks. We will use the quarterly US current account to GDP ratio to compare results from a number of unit root test found in the GAUSS tspdlib library including the: Zivot-Andrews (1992) unit root test with a single structural break, Narayan and Popp (2010) unit root test with two structural breaks, Lee and Strazicich (2013, 2003) LM tests with one and two structural breaks, Enders and Lee Fourier (2012) ADF and LM tests.
Running publicly available GAUSS code: Part 2
This week’s blog brings you the second video in the series examining running publicly available GAUSS code. This video runs the popular code by Hatemi-J for testing cointegration with multiple structural breaks. In this video you will learn how to:
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- Substitute your own dataset.
- Modify the indexing commands for your data.
- Remove missing values.
- Preview your data after loading with the Ctrl+E keyboard shortcut.
Running publicly available GAUSS code: Part 1
This blog explores how to use publicly available GAUSS code in your own GAUSS projects. This video will guide you through:
- Opening your code in the Project Folders Window.
- Running the code.
- The Applications Installer.
- Setting your working directory.
- Error G0290 Library not found.
- Error G0014 File not found.
- Viewing workspace variables.
The Basics of Quantile Regression
Classical linear regression estimates the mean response of the dependent variable dependent on the independent variables. There are many cases, such as skewed data, multimodal data, or data with outliers, when the behavior at the conditional mean fails to fully capture the patterns in the data. In these cases, quantile regression provides a useful alternative to linear regression. Today we explore quantile regression and use the GAUSS quantileFit procedure to analyze Major League Baseball Salary data.
Basic Bootstrapping in GAUSS
The bootstrap is a commonly used resampling technique which involves taking random samples with replacement to quantify uncertainty about a particular estimator or statistic. In this post, we will walk the how to apply the bootstrap procedure using asset returns.
Top five hotkeys to get more done in GAUSS
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:
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- Quickly view data symbols using
Ctrl+E. - Open floating command reference pages using
Shift+F1. - Toggle block comments on and off using
Ctrl+/. - Go to procedure definitions using
Ctrl+F1. - Delete lines using
Ctrl+L.
Permutation Entropy
Permutation Entropy (PE) is a robust time series tool which provides a quantification measure of the complexity of a dynamic system by capturing the order relations between values of a time series and extracting a probability distribution of the ordinal patterns (see Henry and Judge, 2019). Today, we will learn about the PE methodology and will demonstrate its use through a toy example.