If you have run much publicly available GAUSS code, you have probably come across the `#include` command. In this blog, we answer some important questions about #include:
What does `#include` do?
What is the most common error when using `#include`?
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.
Autocomplete is becoming a common feature in the tools we use in all aspects of our lives, because of it’s ability to help us to type more accurately and quickly. When programming in GAUSS, the autocomplete can also show you new functions you were not aware of. Today we will discuss how to use and control autocomplete features of the GAUSS editor and command window.
The key to getting the most performance from a matrix language is to vectorize your code as much as possible. Vectorized code performs operations on large sections of matrices and vectors in a single operation, rather than looping over the elements one-by-one. In this blog, we learn how to use the GAUSS recserar function to vectorize code and simulate a time series AR(1) model.
Starting in GAUSS version 12, a new suite of high quality and high-performance random number generators was introduced. While new projects should always use one of the modern RNG’s, it is sometimes necessary to exactly reproduce some work from the past. GAUSS has retained a set of older LCG’s, which will allow you to reproduce the random numbers from older GAUSS versions for many distributions.
