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Semiparametric regression with R
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...
Autores principales: | , , |
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Lenguaje: | eng |
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Springer
2018
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-1-4939-8853-2 http://cds.cern.ch/record/2653100 |
_version_ | 1780961016151015424 |
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author | Harezlak, Jaroslaw Ruppert, David Wand, Matt P |
author_facet | Harezlak, Jaroslaw Ruppert, David Wand, Matt P |
author_sort | Harezlak, Jaroslaw |
collection | CERN |
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. |
id | cern-2653100 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2018 |
publisher | Springer |
record_format | invenio |
spelling | cern-26531002021-04-21T18:37:33Zdoi:10.1007/978-1-4939-8853-2http://cds.cern.ch/record/2653100engHarezlak, JaroslawRuppert, DavidWand, Matt PSemiparametric regression with RMathematical Physics and MathematicsThis 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.Springeroai:cds.cern.ch:26531002018 |
spellingShingle | Mathematical Physics and Mathematics Harezlak, Jaroslaw Ruppert, David Wand, Matt P Semiparametric regression with R |
title | Semiparametric regression with R |
title_full | Semiparametric regression with R |
title_fullStr | Semiparametric regression with R |
title_full_unstemmed | Semiparametric regression with R |
title_short | Semiparametric regression with R |
title_sort | semiparametric regression with r |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-1-4939-8853-2 http://cds.cern.ch/record/2653100 |
work_keys_str_mv | AT harezlakjaroslaw semiparametricregressionwithr AT ruppertdavid semiparametricregressionwithr AT wandmattp semiparametricregressionwithr |