Statistics for High-Dimensional Data

Methods, Theory and Applications

Authors:

ISBN: 978-3-642-20191-2 (Print) 978-3-642-20192-9 (Online)

Table of contents (14 chapters)

  1. Front Matter

    Pages i-xvii

  2. No Access

    Book Chapter

    Pages 1-6

    Introduction

  3. No Access

    Book Chapter

    Pages 7-43

    Lasso for linear models

  4. No Access

    Book Chapter

    Pages 45-53

    Generalized linear models and the Lasso

  5. No Access

    Book Chapter

    Pages 55-76

    The group Lasso

  6. No Access

    Book Chapter

    Pages 77-97

    Additive models and many smooth univariate functions

  7. No Access

    Book Chapter

    Pages 99-182

    Theory for the Lasso

  8. No Access

    Book Chapter

    Pages 183-247

    Variable selection with the Lasso

  9. No Access

    Book Chapter

    Pages 249-291

    Theory for ℓ1/ℓ2-penalty procedures

  10. No Access

    Book Chapter

    Pages 293-338

    Non-convex loss functions and ℓ1-regularization

  11. No Access

    Book Chapter

    Pages 339-358

    Stable solutions

  12. No Access

    Book Chapter

    Pages 359-386

    P-values for linear models and beyond

  13. No Access

    Book Chapter

    Pages 387-431

    Boosting and greedy algorithms

  14. No Access

    Book Chapter

    Pages 433-480

    Graphical modeling

  15. No Access

    Book Chapter

    Pages 481-538

    Probability and moment inequalities

  16. Back Matter

    Pages 539-556