Covers conditional distributions and correlations in multivariate statistics, including partial variance and covariance, with applications to non-normal distributions.
Explores portfolio optimization models and strategies under uncertainty, emphasizing decision criteria like value-at-risk and mean-variance functional.
Covers ensemble methods like random forests and Gaussian Naive Bayes, explaining how they improve prediction accuracy and estimate conditional Gaussian distributions.