Semiparametric Regression with R

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Éditeur :

Springer


Collection :

Use R!

Paru le : 2018-12-12

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Description

This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice. Semiparametric regression has a large literature but much of it is geared towards data analysts who have advanced knowledge of statistical methods. While R now has a great deal of semiparametric regression functionality, many of these developments have not trickled down to rank-and-file statistical analysts. 


The authors assemble a broad range of semiparametric regression R analyses and put them in a form that is useful for applied researchers. There are chapters devoted to penalized spines, generalized additive models, grouped data, bivariate extensions of penalized spines, and spatial semi-parametric regression models. Where feasible, the R code is provided in the text, however the book is also accompanied by an external website complete with datasets and R code. Because of its flexibility, semiparametric regression has proven to be of great value with many applications in fields as diverse as astronomy, biology, medicine, economics, and finance. This book is intended for applied statistical analysts who have some familiarity with R.

Pages
331 pages
Collection
Use R!
Parution
2018-12-12
Marque
Springer
EAN papier
9781493988518
EAN PDF
9781493988532

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
20982 Ko
Prix
137,14 €
EAN EPUB
9781493988532

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
80763 Ko
Prix
137,14 €