SAS has more than 25 common probability distributions that are supported in the PDF, CDF, QUANTILE, and RAND functions. If you want to work with a less common distribution, you can implement these functions yourself. For example, I previously showed how to use PROC FCMP in Base SAS to implement
The classical multivariate normal (MVN) distribution is a standard model for correlated data. It is a simple model, it is easy to fit the MVN model to data, and the parameters in the model (locations and correlations) are intuitive. Of course, normality is a strong assumption that is not always
In a previous article, I implemented an algorithm due to Niels Waller (TAS, 2020) that uses the method of alternating projections (MAP) to generate random correlation matrices that have a specified set of eigenvalues. The algorithm is iterative, and the MAP method is not guaranteed to converge, although Waller claims
