A general class of powerful and flexible modeling techniques, spline smoothing has attracted a great deal of research attention in recent years and has been widely used in many application areas, from medicine to economics. Smoothing Splines: Methods and Applications covers basic smoothing spline models, including polynomial, periodic, spherical, t

Yuedong Wang is a professor and the chair of the Department of Statistics and Applied Probability at the University of California-Santa Barbara. Dr. Wang is an elected fellow of the ASA and ISI, a fellow of the RSS, and a member of IMS, IBS, and ICSA. His research covers the development of statistical methodology and its applications.

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.