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Semiparametric Regression with R [[electronic resource] /] / by Jaroslaw Harezlak, David Ruppert, Matt P. Wand



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Autore: Harezlak Jaroslaw Visualizza persona
Titolo: Semiparametric Regression with R [[electronic resource] /] / by Jaroslaw Harezlak, David Ruppert, Matt P. Wand Visualizza cluster
Pubblicazione: New York, NY : , : Springer New York : , : Imprint : Springer, , 2018
Edizione: 1st ed. 2018.
Descrizione fisica: 1 online resource (341 pages)
Disciplina: 519.536
Soggetto topico: Statistics 
R (Computer program language)
Statistical Theory and Methods
Statistics for Life Sciences, Medicine, Health Sciences
Statistics for Business, Management, Economics, Finance, Insurance
Persona (resp. second.): RuppertDavid
WandMatt P
Nota di contenuto: Introduction -- Penalized Splines -- Generalized Additive Models -- Semiparametric Regression Analysis of Grouped Data -- Bivariate Function Extensions -- Selection of Additional Topics.-Index.
Sommario/riassunto: This easy-to-follow applied book expands upon the authors’ prior work on semiparametric regression to include the use of R software. In 2003, authors Ruppert and Wand co-wrote Semiparametric Regression with R.J. Carroll, which introduced the techniques and benefits of semiparametric regression in a concise and user-friendly fashion. Fifteen years later, semiparametric regression is applied widely, powerful new methodology is continually being developed, and advances in the R computing environment make it easier than ever before to carry out analyses. Semiparametric Regression with R introduces the basic concepts of semiparametric regression with a focus on applications and R software. This volume features case studies from environmental, economic, financial, and other fields. The examples and corresponding code can be used or adapted to apply semiparametric regression to a wide range of problems. It contains more than fifty exercises, and the accompanying HRW package contains all datasets and scripts used in the book, as well as some useful R functions. This book is suitable as a textbook for advanced undergraduates and graduate students, as well as a guide for statistically-oriented practitioners, and could be used in conjunction with Semiparametric Regression. Readers are assumed to have a basic knowledge of R and some exposure to linear models. For the underpinning principles, calculus-based probability, statistics, and linear algebra are desirable.
Titolo autorizzato: Semiparametric Regression with R  Visualizza cluster
ISBN: 1-4939-8853-0
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910303452503321
Lo trovi qui: Univ. Federico II
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Serie: Use R!, . 2197-5736