Chong Gu

Smoothing Spline ANOVA Models (eBook, PDF)

• Format: PDF

Produktbeschreibung

Smoothing methods are an active area of research. In this book, the author presents a comprehensive treatment of penalty smoothing under a unified framework. Methods are developed for (i) regression with Gaussian and non-Gaussian responses as well as with censored life time data; (ii) density and conditional density estimation under a variety of sampling schemes; and (iii) hazard rate estimation with censored life time data and covariates. Extensive discussions are devoted to model construction, smoothing parameter selection, computation, and asymptotic convergence. Most of the computational and data analytical tools discussed in the book are implemented in R, an open-source clone of the popular S/S- PLUS language.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer US
• Seitenzahl: 290
• Erscheinungstermin: 9. März 2013
• Englisch
• ISBN-13: 9781475736830
• Artikelnr.: 44053796

Autorenporträt

Chong Gu received his Ph.D. from University of Wisconsin-Madison in 1989, and has been on the faculty in Department of Statistics, Purdue University since 1990. At various times during his career, he has held visiting appointments at University of British Columbia, University of Michigan, and National Institute of Statistical Sciences.

Inhaltsangabe

Introduction.- Model Construction.- Regression with Gaussian-Type Responses.- More Splines.- Regression and Exponential Families.- Regression with Correlated Responses.- Probability Density Estimation.- Hazard Rate Estimation.- Asymptotic Convergence.- Penalized Pseudo Likelihood.

Rezensionen

"The purpose of the book is to comprehensively present smoothing and penalized splines from the point of view of reproducing kernel Hilbert spaces (RKHS). ... the book makes a valuable contribution to the literature on smoothing and penalized splines, especially for more mathematically oriented researchers." (W. John Braun, Technometrics, Vol. 56 (4), November, 2014)