Handbook of regression analysis with applications in R:
"Building on the Handbook of Regression Analysis and Regression Analysis by Example, the authors' thorough treatments of "classic" regression analysis, this book covers two important and more advanced topics of time-to-event survival data and longitudinal and clustered data. Furt...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, NJ
Wiley
2020
|
| Ausgabe: | Second edition |
| Schriftenreihe: | Wiley series in probability and statistics
|
| Schlagworte: | |
| Online-Zugang: | UBY01 Volltext |
| Zusammenfassung: | "Building on the Handbook of Regression Analysis and Regression Analysis by Example, the authors' thorough treatments of "classic" regression analysis, this book covers two important and more advanced topics of time-to-event survival data and longitudinal and clustered data. Further, methods that have become prominent in the last 15-30 years that are designed for analyses on often-large data sets and can take advantage of exibility in modeling were not covered, including smoothing, tree- based, and regularization methods, all of which are increasingly becoming part of the data analysis toolkit. Examples are drawn from a wide variety of application areas using real data sets and all of the R code is provided. The book will be of interest to data scientists as well as in regression analysis courses at the graduate and undergraduate level. Regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables -- that is, the average value of the dependent variable when the independent variables are fixed. Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning"--.. |
| Beschreibung: | Revised edition of: Handbook of regression analysis Includes bibliographical references and index Description based on print version record and CIP data provided by publisher; resource not viewed |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9781119392491 1119392497 9781119392484 1119392489 9781119392477 1119392470 |
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| 245 | 1 | 0 | |a Handbook of regression analysis with applications in R |c Professor Samprit Chatterjee, New York University, Professor Jeffrey S. Simonoff, New York University |
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| edition | Second edition |
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| id | DE-604.BV047190630 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:47:47Z |
| indexdate | 2024-07-10T09:05:11Z |
| institution | BVB |
| isbn | 9781119392491 1119392497 9781119392484 1119392489 9781119392477 1119392470 |
| language | English |
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| publishDate | 2020 |
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| publisher | Wiley |
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| series2 | Wiley series in probability and statistics |
| spelling | Chatterjee, Samprit 1938- Verfasser (DE-588)172018978 aut Handbook of regression analysis Handbook of regression analysis with applications in R Professor Samprit Chatterjee, New York University, Professor Jeffrey S. Simonoff, New York University Second edition Hoboken, NJ Wiley 2020 Hoboken, NJ John Wiley & Sons, Inc 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Wiley series in probability and statistics Revised edition of: Handbook of regression analysis Includes bibliographical references and index Description based on print version record and CIP data provided by publisher; resource not viewed "Building on the Handbook of Regression Analysis and Regression Analysis by Example, the authors' thorough treatments of "classic" regression analysis, this book covers two important and more advanced topics of time-to-event survival data and longitudinal and clustered data. Further, methods that have become prominent in the last 15-30 years that are designed for analyses on often-large data sets and can take advantage of exibility in modeling were not covered, including smoothing, tree- based, and regularization methods, all of which are increasingly becoming part of the data analysis toolkit. Examples are drawn from a wide variety of application areas using real data sets and all of the R code is provided. The book will be of interest to data scientists as well as in regression analysis courses at the graduate and undergraduate level. Regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables -- that is, the average value of the dependent variable when the independent variables are fixed. Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning"--.. R Programm (DE-588)4705956-4 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 s R Programm (DE-588)4705956-4 s DE-604 Simonoff, Jeffrey S. 1955- Verfasser (DE-588)17080867X aut 9781119392378 Erscheint auch als Druck-Ausgabe 1119392470 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119392491 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Chatterjee, Samprit 1938- Simonoff, Jeffrey S. 1955- Handbook of regression analysis with applications in R R Programm (DE-588)4705956-4 gnd Regressionsanalyse (DE-588)4129903-6 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4129903-6 |
| title | Handbook of regression analysis with applications in R |
| title_alt | Handbook of regression analysis |
| title_auth | Handbook of regression analysis with applications in R |
| title_exact_search | Handbook of regression analysis with applications in R |
| title_exact_search_txtP | Handbook of regression analysis with applications in R |
| title_full | Handbook of regression analysis with applications in R Professor Samprit Chatterjee, New York University, Professor Jeffrey S. Simonoff, New York University |
| title_fullStr | Handbook of regression analysis with applications in R Professor Samprit Chatterjee, New York University, Professor Jeffrey S. Simonoff, New York University |
| title_full_unstemmed | Handbook of regression analysis with applications in R Professor Samprit Chatterjee, New York University, Professor Jeffrey S. Simonoff, New York University |
| title_short | Handbook of regression analysis with applications in R |
| title_sort | handbook of regression analysis with applications in r |
| topic | R Programm (DE-588)4705956-4 gnd Regressionsanalyse (DE-588)4129903-6 gnd |
| topic_facet | R Programm Regressionsanalyse |
| url | https://onlinelibrary.wiley.com/doi/book/10.1002/9781119392491 |
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