Multivariate Statistics Classical Foundations And Modern Machine Learning By Hemant Ishwaran Newly Released For The 2026/2027 Academic Year
Master multivariate statistics with this comprehensive guide by Dr. Hemant Ishwaran, bridging classical methods like MANOVA and PCA with modern machine learning techniques such as random forests, gradient boosting, and causal inference. This resource explores the theoretical underpinnings of empirical risk minimization and regularization while offering practical applications in public health and medicine. Ideal for students and researchers seeking a unified approach to statistical learning theory, this text includes extensive exercises on super greedy trees, variable selection, and survival analysis models.
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