Semiparametric Regression with R

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Special Collection:e-book
Format: Book
Language:English
Published: New York, NY : : Springer New York : Imprint: Springer,, 2018
Edition:1st ed. 2018.
Series:Use R!,, ISSN 2197-5736
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Online Access:https://doi.org/10.1007/978-1-4939-8853-2
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Item Description: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.
Physical Description:XI, 331 p. 144 illus., 142 illus. in color. : online forrás
ISBN:978-1-4939-8853-2
ISSN:2197-5736