02045nam a22002657a 4500003000800000005001700008007000300025008004100028020001800069040002100087082001600108100001900124245007600143250001200219260004000231300001500271490003300286504003200319505027700351520098800628650001801616650003001634856004301664856007201707arcduce20211025132642.0t|121101s2017 flu||||| |||| 00| 0 eng d a9781498728331 aarcducecarcduce0 222a519.2821 aWood, Simon N.10aGeneralized additive models :ban introduction with R /cSimon N. Wood. a2nd ed. aBoca Raton, Fl. :bCRC Press,c2017 axx, 476 p.0 aTexts in statistical science aBibliografía: p. 455-465.0 aPreface -- 1. Linear models -- 2. Linear models -- 3. Generalized linear models -- 4. Introducing GAMs -- 5. Smoothers -- 6. GAM theory -- 7. GAMs in practice: mgcv -- A: Maximum likelihood estimation -- B: Some matrix algebra -- C: Solutions to exercises -- Bibliography.3 aThe first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before presenting a balanced treatment of the theory and applications of GAMs and related models.
The author bases his approach on a framework of penalized regression splines, and while firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of R software helps explain the theory and illustrates the practical application of the methodology. Each chapter contains an extensive set of exercises, with solutions in an appendix or in the book’s R data package gamair, to enable use as a course text or for self-study. 4aMODELO LINEAL 4aEJERCICIOS DE ESTADISTICA4 uhttps://ar1lib.org/book/3553646/73cc0c4 uhttps://orcid.org/0000-0002-2034-7453yInformación sobre el autor