Mixed models: theory and applications with R
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hoboken
Wiley
2013
|
| Ausgabe: | 2nd ed |
| Schlagworte: | |
| Beschreibung: | Includes bibliographical references and index "Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. The new edition includes significant updating, over 300 exercises, stimulating chapter projects and model simulations, inclusion of R subroutines, and a revised text format. The target audience continues to be graduate students and researchers. An author-maintained web site is available with solutions to exercises and a compendium of relevant data sets"-- |
| Beschreibung: | xxvii, 717 p. |
| ISBN: | 9781118593066 |
Internformat
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| 100 | 1 | |a Demidenko, Eugene |d 1948- |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Mixed models |b theory and applications with R |c Eugene Demidenko |
| 250 | |a 2nd ed | ||
| 264 | 1 | |a Hoboken |b Wiley |c 2013 | |
| 300 | |a xxvii, 717 p. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
| 500 | |a "Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. The new edition includes significant updating, over 300 exercises, stimulating chapter projects and model simulations, inclusion of R subroutines, and a revised text format. The target audience continues to be graduate students and researchers. An author-maintained web site is available with solutions to exercises and a compendium of relevant data sets"-- | ||
| 505 | 0 | |a Machine generated contents note: Preface xviiPreface to the Second Edition xixR software and functions xxData Sets xxiiOpen Problems in Mixed Models xxiii1 Introduction: Why Mixed Models? 11.1 Mixed effects for clustered data 21.2 ANOVA, variance components, and the mixed model 41.3 Other special cases of the mixed effects model 61.4 A compromise between Bayesian and frequentist approaches 71.5 Penalized likelihood and mixed effects 91.6 Healthy Akaike information criterion 111.7 Penalized smoothing 131.8 Penalized polynomial fitting 161.9 Restraining parameters, or what to eat 181.10 Ill-posed problems, Tikhonov regularization, | |
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Datensatz im Suchindex
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|---|---|
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| author | Demidenko, Eugene 1948- |
| author_facet | Demidenko, Eugene 1948- |
| author_role | aut |
| author_sort | Demidenko, Eugene 1948- |
| author_variant | e d ed |
| building | Verbundindex |
| bvnumber | BV044177734 |
| classification_rvk | QH 233 |
| collection | ZDB-30-PAD |
| contents | Machine generated contents note: Preface xviiPreface to the Second Edition xixR software and functions xxData Sets xxiiOpen Problems in Mixed Models xxiii1 Introduction: Why Mixed Models? 11.1 Mixed effects for clustered data 21.2 ANOVA, variance components, and the mixed model 41.3 Other special cases of the mixed effects model 61.4 A compromise between Bayesian and frequentist approaches 71.5 Penalized likelihood and mixed effects 91.6 Healthy Akaike information criterion 111.7 Penalized smoothing 131.8 Penalized polynomial fitting 161.9 Restraining parameters, or what to eat 181.10 Ill-posed problems, Tikhonov regularization, |
| ctrlnum | (ZDB-30-PAD)EBC1365053 (ZDB-89-EBL)EBL1365053 (OCoLC)835118592 (DE-599)BVBBV044177734 |
| dewey-full | 519.5/38 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5/38 |
| dewey-search | 519.5/38 |
| dewey-sort | 3519.5 238 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | 2nd ed |
| format | Electronic eBook |
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| indexdate | 2024-07-10T07:45:53Z |
| institution | BVB |
| isbn | 9781118593066 |
| language | English |
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| physical | xxvii, 717 p. |
| psigel | ZDB-30-PAD |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Wiley |
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| spelling | Demidenko, Eugene 1948- Verfasser aut Mixed models theory and applications with R Eugene Demidenko 2nd ed Hoboken Wiley 2013 xxvii, 717 p. txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index "Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. The new edition includes significant updating, over 300 exercises, stimulating chapter projects and model simulations, inclusion of R subroutines, and a revised text format. The target audience continues to be graduate students and researchers. An author-maintained web site is available with solutions to exercises and a compendium of relevant data sets"-- Machine generated contents note: Preface xviiPreface to the Second Edition xixR software and functions xxData Sets xxiiOpen Problems in Mixed Models xxiii1 Introduction: Why Mixed Models? 11.1 Mixed effects for clustered data 21.2 ANOVA, variance components, and the mixed model 41.3 Other special cases of the mixed effects model 61.4 A compromise between Bayesian and frequentist approaches 71.5 Penalized likelihood and mixed effects 91.6 Healthy Akaike information criterion 111.7 Penalized smoothing 131.8 Penalized polynomial fitting 161.9 Restraining parameters, or what to eat 181.10 Ill-posed problems, Tikhonov regularization, Analysis of variance Varianzanalyse (DE-588)4187413-4 gnd rswk-swf Gemischtes Modell (DE-588)4156565-4 gnd rswk-swf R Programm (DE-588)4705956-4 gnd rswk-swf Gemischtes Modell (DE-588)4156565-4 s R Programm (DE-588)4705956-4 s 1\p DE-604 Varianzanalyse (DE-588)4187413-4 s 2\p DE-604 Erscheint auch als Druck-Ausgabe, Hardcover 978-1-118-09157-9 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Demidenko, Eugene 1948- Mixed models theory and applications with R Machine generated contents note: Preface xviiPreface to the Second Edition xixR software and functions xxData Sets xxiiOpen Problems in Mixed Models xxiii1 Introduction: Why Mixed Models? 11.1 Mixed effects for clustered data 21.2 ANOVA, variance components, and the mixed model 41.3 Other special cases of the mixed effects model 61.4 A compromise between Bayesian and frequentist approaches 71.5 Penalized likelihood and mixed effects 91.6 Healthy Akaike information criterion 111.7 Penalized smoothing 131.8 Penalized polynomial fitting 161.9 Restraining parameters, or what to eat 181.10 Ill-posed problems, Tikhonov regularization, Analysis of variance Varianzanalyse (DE-588)4187413-4 gnd Gemischtes Modell (DE-588)4156565-4 gnd R Programm (DE-588)4705956-4 gnd |
| subject_GND | (DE-588)4187413-4 (DE-588)4156565-4 (DE-588)4705956-4 |
| title | Mixed models theory and applications with R |
| title_auth | Mixed models theory and applications with R |
| title_exact_search | Mixed models theory and applications with R |
| title_full | Mixed models theory and applications with R Eugene Demidenko |
| title_fullStr | Mixed models theory and applications with R Eugene Demidenko |
| title_full_unstemmed | Mixed models theory and applications with R Eugene Demidenko |
| title_short | Mixed models |
| title_sort | mixed models theory and applications with r |
| title_sub | theory and applications with R |
| topic | Analysis of variance Varianzanalyse (DE-588)4187413-4 gnd Gemischtes Modell (DE-588)4156565-4 gnd R Programm (DE-588)4705956-4 gnd |
| topic_facet | Analysis of variance Varianzanalyse Gemischtes Modell R Programm |
| work_keys_str_mv | AT demidenkoeugene mixedmodelstheoryandapplicationswithr |