The determinant of a matrix arises in many statistical computations, such as in estimating parameters that fit a distribution to multivariate data. For example, if you are using a log-likelihood function to fit a multivariate normal distribution, the formula for the log-likelihood involves the expression log(det(Σ)), where Σ is the
This article is an excerpt from my forthcoming book Simulating Data with SAS. Not every matrix with 1 on the diagonal and off-diagonal elements in the range [–1, 1] is a valid correlation matrix. A correlation matrix has a special property known as positive semidefiniteness. All correlation matrices are positive
Magic squares are cool. Algorithms that create magic squares are even cooler. You probably remember magic squares from your childhood: they are n x n matrices that contain the numbers 1,2,...,n2 and for which the row sum, column sum, and the sum of both diagonals are the same value. There are many
