I blog about a lot of topics, but the following five categories represent some of my favorite subjects. Judging by the number of readers and comments, these articles have struck a chord with SAS users. If you haven't read them, check them out. (If you HAVE read them, some are worth re-reading!)
- SIMULATION: If you run simulations in SAS, you had better understand the four essential functions for statistical programmers. Simulation depends on random samples, so it is good to know how to generate random numbers in SAS. Lastly, it is important to understand random number streams in SAS and how they work.
- MATRIX COMPUTATIONS: In the article "Solving linear systems: Which technique is fastest?" I show that solving a specific linear system is about four times faster than solving for a general inverse. This article also inspired the popular article, "What is the chance that a random matrix is singular?"
- STATISTICAL PROGRAMMING: You can't program something if you don't understand it. In the article "What is Mahalanobis distance?" I describe the geometry of Mahalanobis distance, which provides a way to measure distances that takes into account correlations in the data. This article is linked to from Wikipedia because it is an "intuitive illustrated explanation." I've also written several other articles related to multivariate statistics:
- Detecting outliers in SAS: Multivariate location and scatter, which desribes how to use SAS software to find multivariate outliers
- How to compute Mahalanobis distance in SAS
- Testing data for multivariate normality, which uses Mahalanobis distance to assess the distribution of multivariate data.
- The curse of dimensionality: How to define outliers in high-dimensional data?