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...
Uloženo v:
| Hlavní autor: | |
|---|---|
| Médium: | Elektronický zdroj E-kniha |
| Jazyk: | angličtina |
| Vydáno: |
New York, NY :
Springer New York ,
2018.
|
| Vydání: | 1st ed. 2018. |
| Edice: | Use R!,
|
| Témata: | |
| ISBN: | 9781493988532 |
| ISSN: | 2197-5736 |
| On-line přístup: |
|
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 003 | SK-BrCVT | ||
| 005 | 20220618103012.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 181212s2018 xxu| s |||| 0|eng d | ||
| 020 | |a 9781493988532 | ||
| 024 | 7 | |a 10.1007/978-1-4939-8853-2 |2 doi | |
| 035 | |a CVTIDW13927 | ||
| 040 | |a Springer-Nature |b eng |c CVTISR |e AACR2 | ||
| 041 | |a eng | ||
| 100 | 1 | |a Harezlak, Jaroslaw. |4 aut | |
| 245 | 1 | 0 | |a Semiparametric Regression with R |h [electronic resource] / |c by Jaroslaw Harezlak, David Ruppert, Matt P. Wand. |
| 250 | |a 1st ed. 2018. | ||
| 260 | 1 | |a New York, NY : |b Springer New York , |c 2018. | |
| 300 | |a XI, 331 p. 144 illus., 142 illus. in color. |b online resource. | ||
| 490 | 1 | |a Use R!, |x 2197-5736 | |
| 500 | |a Mathematics and Statistics | ||
| 505 | 0 | |a Introduction -- Penalized Splines -- Generalized Additive Models -- Semiparametric Regression Analysis of Grouped Data -- Bivariate Function Extensions -- Selection of Additional Topics.-Index. | |
| 516 | |a text file PDF | ||
| 520 | |a 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. | ||
| 650 | 0 | |a Statistics . | |
| 856 | 4 | 0 | |u http://hanproxy.cvtisr.sk/han/cvti-ebook-springer-eisbn-978-1-4939-8853-2 |y Vzdialený prístup pre registrovaných používateľov |
| 910 | |b ZE11207 | ||
| 919 | |a 978-1-4939-8853-2 | ||
| 974 | |a andrea.lebedova |f Elektronické zdroje | ||
| 992 | |a SUD | ||
| 999 | |c 243625 |d 243625 | ||