Graphical models provide a robust framework for representing the conditional independence structure between variables through networks, enabling nuanced insight into complex high-dimensional data.
If you're not familiar with PCA, most of the terminology -- covariance matrix, eigenvalues and eigenvectors and so on -- sounds quite mysterious. But the ideas will become clear shortly. [Click on ...
Froot, K. A. "Consistent Covariance Matrix Estimation with Cross-Sectional Dependence and Heteroskedasticity in Cross-Sectional Financial Data." Journal of Financial and Quantitative Analysis 24, no.
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