About this blog
Rick Wicklin, PhD, is a senior researcher in computational statistics at SAS and is a principal developer of PROC IML and SAS/IML Studio. His areas of expertise include computational statistics, statistical graphics, and modern methods in statistical data analysis. Rick is author of the book Statistical Programming with SAS/IML Software.
Follow @RickWicklin on Twitter.
The curious case of random eigenvalues
I’ve been a fan of statistical simulation and other kinds of computer experimentation for many years. For me, simulation is a good way to understand how the world of statistics works, and to formulate and test conjectures. Last week, while investigating the efficiency of the power method for finding dominant [...]
Post a Comment The power method: compute only the largest eigenvalue of a matrix
When I was at SAS Global Forum last week, a SAS user asked my advice regarding a SAS/IML program that he wrote. One step of the program was taking too long to run and he wondered if I could suggest a way to speed it up. The long-running step was [...]
Post a Comment Generate a random matrix with specified eigenvalues
In a previous post I showed how to implement Stewart’s (1980) algorithm for generating random orthogonal matrices in SAS/IML software. By using the algorithm, it is easy to generate a random matrix that contains a specified set of eigenvalues. If D = diag(λ1, …, λp) is a diagonal matrix and [...]
Post a Comment Generating a random orthogonal matrix
Because I am writing a new book about simulating data in SAS, I have been doing a lot of reading and research about how to simulate various quantities. Random integers? Check! Random univariate samples? Check! Random multivariate samples? Check! Recently I’ve been researching how to generate random matrices. I’ve blogged [...]
Post a Comment Defining banded and triangular matrices: Another approach
Sometimes in matrix computations you need to obtain the values of certain submatrices such as the diagonal elements or the super- or subdiagonal elements. About a year ago, I showed one way to do that: convert subscripts to indices and vice-versa. However, a tip from @RLangTip on Twitter got me [...]
Post a Comment How to compute Mahalanobis distance in SAS
I recently blogged about Mahalanobis distance and what it means geometrically. I also previously showed how Mahalanobis distance can be used to compute outliers in multivariate data. But how do you compute Mahalanobis distance in SAS? Computing Mahalanobis distance with built-in SAS procedures and functions There are several ways to [...]
Post a Comment Convert a covariance matrix to a correlation matrix in SAS
I have previously blogged about how to convert a covariance matrix into a correlation matrix in SAS (and the other way around). However, I still get questions about it, perhaps because my previous post demonstrated more than one way to accomplish each transformation. To eliminate all confusion, the following SAS/IML [...]
Post a Comment Use the Cholesky transformation to correlate and uncorrelate variables
A variance-covariance matrix expresses linear relationships between variables. Given the covariances between variables, did you know that you can write down an invertible linear transformation that “uncorrelates” the variables? Conversely, you can transform a set of uncorrelated variables into variables with given covariances. The transformation that works this magic is [...]
Post a Comment Computing the diagonal elements of a product of matrices
Once again I rediscovered something that I once knew, but had forgotten. Fortunately, this blog is a good place to share little code snippets that I don’t want to forget. I needed to compute the diagonal elements of a product of two matrices. In symbols, I have an nxp matrix, [...]
Post a Comment Matrices and mattresses
Birds migrate south in the fall. Squirrels gather nuts. Humans also have behavioral rituals in the autumn. I change the batteries in my smoke detectors, I switch my clocks back to daylight standard time, and I turn the mattress on my bed. The first two are relatively easy. There’s even [...]
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