Inverting a matrix is one of the most common tasks in data science and machine learning. In this article I explain why inverting a matrix is very difficult and present code that you can use as-is, or ...

Matrix decomposition is an area of linear algebra which is focused on expressing a matrix as a product of matrices with prescribed properties. (Photo credit: Merino et al., 2024) Imagine discovering ...

This paper gives a matrix approach to determine when a statistical dependence between two manifest categorical random variables can be viewed as generated by some unobserved latent variables, in the ...

An important problem in multivariate statistics is the estimation of covariance matrices. We consider a class of nonparametric covariance models in which the entries in the covariance matrix depend on ...