Theory of matrix variate distributions extends classical univariate and multivariate approaches to random matrices, accommodating dependence structures across both rows and columns. Fundamental ...
Graphical models provide a robust framework for representing the conditional independence structure between variables through networks, enabling nuanced insight into complex high-dimensional data.
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