Semiparametric Regression with R (Paperback, 1st ed. 2018)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Use R!
Release date:	December 2018
First published:	2018
Authors:	Jaroslaw Harezlak • David Ruppert • Matt P. Wand
Dimensions:	235 x 155 x 26mm (L x W x T)
Format:	Paperback
Pages:	331
Edition:	1st ed. 2018
ISBN-13:	978-1-4939-8851-8
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software Promotions
LSN:	1-4939-8851-4
Barcode:	9781493988518

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