A Course in Regression and Smoothing Methods (True PDF)

A Course in Regression and Smoothing Methods (True PDF)

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English | 2026 | ISBN: 1041152779 | 289 pages | True PDF | 11.32 MB
This book provides a concise account of four components of regression and smoothing methods: linear regression, generalized linear models, spline and kernel methods, and generalized linear mixed models. By bringing together parametric regression and nonparametric smoothing methods, the book emphasizes connections across methods, enabling readers to recognize common structures and to adapt techniques to new problems.
While standard texts often focus on the application of statistical methods from a user's perspective, this book covers the foregoing topics from a developer's perspective, with systematic attention to the mathematical, statistical, and computational ideas and results that underlie the methods. The distinction is analogous to that between a user’s manual and a developer’s manual for software: the goal is not only to nstrate how to apply the methods, but also how they are derived and implemented.