Screen LibraryMixed models : theory and applications with R /
"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 nume...
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| Main Authors: | |
|---|---|
| Published: |
Wiley,
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| Publisher Address: | Hoboken : |
| Publication Dates: | 2013. |
| Literature type: | eBook |
| Language: | English |
| Edition: | Second [edition]. |
| Series: |
Wiley series in probability and statistics ;
893 |
| Subjects: | |
| Online Access: |
http://onlinelibrary.wiley.com/book/10.1002/9781118651537 |
| Summary: |
"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 b |
| Carrier Form: | 1 online resource. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9781118592991 (epub) 1118592999 (epub) 9781118593066 (pdf) 1118593065 (pdf) 9781118593011 ( mobi) 1118593014 ( mobi) 9781118651537 1118651537 |
| Access: | Due to publisher license, access is restricted to authorised GRAIL clients only. Please contact GRAIL staff. |
| Index Number: | QA279 |
| CLC: | O212.1 |
| Contents: | Preface -- Preface to the Second Edition -- R software and functions -- Data Sets -- Open Problems in Mixed Models -- 1. Introduction: Why Mixed Models? -- 2. MLE for the LME Model -- 3. Statistical Properties of the LME Model -- 4. Growth Curve Model and Generalizations -- 5. Meta-analysis Model -- 6. Nonlinear Marginal Model -- 7. Generalized Linear Mixed Models -- 8. Nonlinear Mixed Effects Model -- 9. Diagnostics and Influence Analysis -- 10. Tumor Regrowth Curves -- 11. Statistical Analysis of Shape -- 12. Statistical Image Analysis -- 13. Appendix: Useful Facts and Formulas. |