Overview

Volume II of this three-volume treatise advances into sophisticated statistical modeling techniques essential for modern risk management. Covering Chapters 16-31 across 490 pages, this volume explores generalised linear models, time series analysis, principal component analysis, decision trees, ensemble methods, and unsupervised learning algorithms. Topics include logistic regression, Poisson regression, ARIMA models, random forests, gradient boosting, k-means clustering, and hierarchical clustering. Each chapter builds systematically on the foundations established in Volume I, with rigorous mathematical derivations complemented by practical applications and fully solved exercises. The integration of the TI-30XS calculator continues throughout, providing computational guidance for complex statistical procedures. Part of a comprehensive 3-volume set (1,548 pages total across 46 chapters) published by The Scottish Science Society.

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