Category: Programming

Fundamental Bayesian Samplers

Introduction The posterior probability distribution is the heart of Bayesian statistics and a fundamental tool for Bayesian parameter estimation. Naturally, how to infer and build these distributions is a widely examined topic, the scope of which cannot fit in one blog. We can, however, start to build a better understanding of sampling by examining three [...]

The Current Working Directory: What you need to know

Introduction Whether you are new to GAUSS, or have been around for a while, today's blog will have something for you. We'll answer the questions: What is the current working directory in GAUSS? How can I find my working directory? How can I change my working directory? Then we'll show you how some common GAUSS [...]

GAUSS Basics 6: Logical and relational operators

Learn how to use the logical and relational operators in GAUSS. These operators include: and, not, or, xor, less-than, less-than or equal, greater-than, greater-than or equal, equal You will also see these operators used to select specific rows of a matrix with logical indexing. Previous: GAUSS Basics 5: Element-by-element conformability

Running publicly available GAUSS code: Part 2

Hatemi code for cointegration with multiple structural breaks   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: Substitute your own dataset. Modify the [...]

Basic Bootstrapping in GAUSS

Introduction The bootstrap is a commonly used resampling technique which involves taking random samples with replacement to quantify uncertainty about a particular estimator or statistic. Goals In this post, we will apply the bootstrap procedure to asset returns. Our data will be annual returns from the S&P 500 and the 10 year US Treasury Bond [...]

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