Smoothing Splines
Methods and Applications
Lieferzeit: Besorgungstitel - Lieferbar innerhalb von 10 Werktagen I
Gewicht:
680 g
Format:
239x160x25 mm
Beschreibung:
With many real-world examples, this book shows how to apply the powerful methods of smoothing splines in practice. It covers basic smoothing spline models as well as more advanced models, such as spline smoothing with correlated random errors. It also presents methods for model selection and inference. The author makes the advanced smoothing spline methodology based on reproducing kernel Hilbert space (RKHS) accessible to practitioners and students by keeping theory to a minimum. R is used throughout to implement the methods, with code available for download on the book's web page.
Introduction. Smoothing Spline Regression. Smoothing Parameter Selection and Inference. Smoothing Spline ANOVA. Spline Smoothing with Heteroscedastic and/or Correlated Errors. Generalized Smoothing Spline ANOVA. Smoothing Spline Nonlinear Regression. Semiparametric Regression. Semiparametric Mixed-Effects Models. Appendices. References. Indices.