Semiparametric Regression with R eBook
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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.

About the book
Author
Jaroslaw  Harezlak , David  Ruppert , Matt P.  Wand
Imprint
Springer
Collection
Use R!
Publication date
2018-12-12
Pages
331 pages
Print ISBN
9781493988518
Language
English
Ebook informations
EAN PDF
9781493988532
Price
£119.50
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Copy count 3
Print count 33
File size 20982 Ko
Ce livre est accessible aux handicaps   Informations accessibility
EAN EPUB
9781493988532
Price
£119.50
Read more
Copy count 3
Print count 33
File size 80763 Ko
Ce livre est accessible aux handicaps   Informations accessibility
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