Data analysis using hierarchical generalized linear models with R:
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton ; London ; New York
CRC Press
[2017]
|
| Schriftenreihe: | A Chapman & Hall Book
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | xii, 321 Seiten Illustrationen, Diagramme |
| ISBN: | 9781138627826 |
Internformat
MARC
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents List of notations ix Preface xi 1 2 3 Introduction 1 1.1 5 Motivating examples 1.2 Regarding criticisms of the h-likelihood 14 1.3 16 R code 1.4 Exercises 17 GLMs via iterativeweighted leastsquares 19 2.1 Examples 19 2.2 R code 25 2.3 Fisher’s classical likelihood 28 2.4 Iterative weighted least squares 30 2.5 Model checking using residual plots 33 2.6 Hat values 33 2.7 Exercises 34 Inference for models withunobservables 37 3.1 Examples 38 3.2 R code 41 3.3 Likelihood inference for random effects 44
vi CONTENTS 3.4 Extended likelihood principle 50 3.5 Laplace approximations for the integrals 53 3.6 Street magician 56 3.7 H-likelihood and empirical Bayes 58 3.8 Exercises 62 4 HGLMs: from method to algorithm 65 4.1 Examples 65 4.2 R code 79 4.3 IWLS algorithm for interconnected GLMs 82 4.4 IWLS algorithm for augmented GLM 85 4.5 IWLS algorithm for HGLMs 86 4.6 Estimation algorithm for a Poisson GLMM 88 4.7 Exercises 91 5 HGLMs modeling in R 95 5.1 Examples 5.2 R code 124 5.3 Exercises 132 6 Double HGLMs - using the dhglm package 95 137 6.1 Model description for DHGLMs 138 6.2 Examples 140 6.3 An extension of linear mixed models via DHGLM 170 6.4 Implementation in the dhglm package 172 6.5 Exercises 175 7 Fitting multivariate HGLMs 177 7.1 Examples 178 7.2 Implementation in the mdhglm package 219 7.3 Exercises 220
CONTENTS 8 vii Survival analysis 223 8.1 Examples 224 8.2 Competing risk models 238 8.3 Comparison with alternative R procedures 241 8.4 H-likelihood theory for the frailty model 244 8.5 Running the frailtyHL package 249 8.6 Exercises 250 9 Joint models 253 9.1 Examp!es 254 9.2 H-likelihood approach to joint models 265 9.3 Exercises 268 10 Further topics 271 10.1 Examples 271 10.2 Variable selections 277 10.3 Examples 288 10.4 Hypothesis testing 291 References 299 Data Index 311 Author Index 313 Subject Index 317
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| adam_txt |
Contents List of notations ix Preface xi 1 2 3 Introduction 1 1.1 5 Motivating examples 1.2 Regarding criticisms of the h-likelihood 14 1.3 16 R code 1.4 Exercises 17 GLMs via iterativeweighted leastsquares 19 2.1 Examples 19 2.2 R code 25 2.3 Fisher’s classical likelihood 28 2.4 Iterative weighted least squares 30 2.5 Model checking using residual plots 33 2.6 Hat values 33 2.7 Exercises 34 Inference for models withunobservables 37 3.1 Examples 38 3.2 R code 41 3.3 Likelihood inference for random effects 44
vi CONTENTS 3.4 Extended likelihood principle 50 3.5 Laplace approximations for the integrals 53 3.6 Street magician 56 3.7 H-likelihood and empirical Bayes 58 3.8 Exercises 62 4 HGLMs: from method to algorithm 65 4.1 Examples 65 4.2 R code 79 4.3 IWLS algorithm for interconnected GLMs 82 4.4 IWLS algorithm for augmented GLM 85 4.5 IWLS algorithm for HGLMs 86 4.6 Estimation algorithm for a Poisson GLMM 88 4.7 Exercises 91 5 HGLMs modeling in R 95 5.1 Examples 5.2 R code 124 5.3 Exercises 132 6 Double HGLMs - using the dhglm package 95 137 6.1 Model description for DHGLMs 138 6.2 Examples 140 6.3 An extension of linear mixed models via DHGLM 170 6.4 Implementation in the dhglm package 172 6.5 Exercises 175 7 Fitting multivariate HGLMs 177 7.1 Examples 178 7.2 Implementation in the mdhglm package 219 7.3 Exercises 220
CONTENTS 8 vii Survival analysis 223 8.1 Examples 224 8.2 Competing risk models 238 8.3 Comparison with alternative R procedures 241 8.4 H-likelihood theory for the frailty model 244 8.5 Running the frailtyHL package 249 8.6 Exercises 250 9 Joint models 253 9.1 Examp!es 254 9.2 H-likelihood approach to joint models 265 9.3 Exercises 268 10 Further topics 271 10.1 Examples 271 10.2 Variable selections 277 10.3 Examples 288 10.4 Hypothesis testing 291 References 299 Data Index 311 Author Index 313 Subject Index 317 |
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| illustrated | Illustrated |
| index_date | 2024-07-03T16:24:35Z |
| indexdate | 2024-07-10T09:02:44Z |
| institution | BVB |
| isbn | 9781138627826 |
| language | English |
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| physical | xii, 321 Seiten Illustrationen, Diagramme |
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| series2 | A Chapman & Hall Book |
| spelling | Lee, Youngjo Verfasser (DE-588)173864414 aut Data analysis using hierarchical generalized linear models with R Youngjo Lee, Lars Rönnegård, Maengseok Noh Boca Raton ; London ; New York CRC Press [2017] © 2017 xii, 321 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier A Chapman & Hall Book Includes bibliographical references and index Linear models (Statistics) Textbooks Multilevel models (Statistics) Textbooks R (Computer program language) Datenanalyse (DE-588)4123037-1 gnd rswk-swf R Programm (DE-588)4705956-4 gnd rswk-swf Datenanalyse (DE-588)4123037-1 s R Programm (DE-588)4705956-4 s DE-604 Rönnegård, Lars Verfasser (DE-588)1228385750 aut Noh, Maengseok Verfasser (DE-588)133610381 aut Erscheint auch als Online-Ausgabe 978-1-351-81155-2 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032511778&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Lee, Youngjo Rönnegård, Lars Noh, Maengseok Data analysis using hierarchical generalized linear models with R Linear models (Statistics) Textbooks Multilevel models (Statistics) Textbooks R (Computer program language) Datenanalyse (DE-588)4123037-1 gnd R Programm (DE-588)4705956-4 gnd |
| subject_GND | (DE-588)4123037-1 (DE-588)4705956-4 |
| title | Data analysis using hierarchical generalized linear models with R |
| title_auth | Data analysis using hierarchical generalized linear models with R |
| title_exact_search | Data analysis using hierarchical generalized linear models with R |
| title_exact_search_txtP | Data analysis using hierarchical generalized linear models with R |
| title_full | Data analysis using hierarchical generalized linear models with R Youngjo Lee, Lars Rönnegård, Maengseok Noh |
| title_fullStr | Data analysis using hierarchical generalized linear models with R Youngjo Lee, Lars Rönnegård, Maengseok Noh |
| title_full_unstemmed | Data analysis using hierarchical generalized linear models with R Youngjo Lee, Lars Rönnegård, Maengseok Noh |
| title_short | Data analysis using hierarchical generalized linear models with R |
| title_sort | data analysis using hierarchical generalized linear models with r |
| topic | Linear models (Statistics) Textbooks Multilevel models (Statistics) Textbooks R (Computer program language) Datenanalyse (DE-588)4123037-1 gnd R Programm (DE-588)4705956-4 gnd |
| topic_facet | Linear models (Statistics) Textbooks Multilevel models (Statistics) Textbooks R (Computer program language) Datenanalyse R Programm |
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