Course Notes for 171:290 Advanced Biostatistcs Seminar: Model Selection

• Lecture I: Introductory Principles, Concepts, and Procedures
• Lecture II: The Akaike Information Criterion
• Lecture III: Corrected AIC and Modified AIC, AICc and MAIC
• Lecture IV: The Takeuchi Information Criterion, TIC
• Lecture V: The Bayesian Information Criterion, BIC
• Lecture VI: The Conceptual Predictive Statistic, Cp
• Lecture VII: Criteria for Regression Model Selection
• Lecture VIII: Criteria for Time Series Model Selection (Part I)
• Lecture IX: Criteria for Time Series Model Selection (Part II)
• Lecture X: Discrepancy-Based Model Selection Criteria
• Lecture XI: Model Selection Criteria Based on Computationally Intensive Complexity Penalizations
• Lecture XII: Model Averaging
• Lecture XIII: Penalized (Ridge) Regression and the LASSO
• Lecture XIV: The Application of Model Selection Criteria