Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Acknowledgments
- Notation
- Part I Classic Statistical Inference
- Part II Early Computer-Age Methods
- Part III Twenty-First-Century Topics
- 15 Large-Scale Hypothesis Testing and FDRs
- 16 Sparse Modeling and the Lasso
- 17 Random Forests and Boosting
- 18 Neural Networks and Deep Learning
- 19 Support-Vector Machines and Kernel Methods
- 20 Inference After Model Selection
- 21 Empirical Bayes Estimation Strategies
- Epilogue
- References
- Author Index
- Subject Index
20 - Inference After Model Selection
from Part III - Twenty-First-Century Topics
Published online by Cambridge University Press: 05 July 2016
Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Acknowledgments
- Notation
- Part I Classic Statistical Inference
- Part II Early Computer-Age Methods
- Part III Twenty-First-Century Topics
- 15 Large-Scale Hypothesis Testing and FDRs
- 16 Sparse Modeling and the Lasso
- 17 Random Forests and Boosting
- 18 Neural Networks and Deep Learning
- 19 Support-Vector Machines and Kernel Methods
- 20 Inference After Model Selection
- 21 Empirical Bayes Estimation Strategies
- Epilogue
- References
- Author Index
- Subject Index
Summary
A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
- Type
- Chapter
- Information
- Computer Age Statistical InferenceAlgorithms, Evidence, and Data Science, pp. 394 - 420Publisher: Cambridge University PressPrint publication year: 2016