High-Dimensional Statistics: A Non-Asymptotic Viewpoint (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 48)
Martin J. Wainwright
- ISBN-13
- Publisher
- Cambridge University Press
- Year
- 2019
- Pages
- 568
- Format
- Hardcover, new
Graduate statistics text by Martin J. Wainwright (Cambridge University Press, 2019). It covers tail bounds, concentration inequalities and random matrices, then sparse linear models and other model classes. Hardcover, 568 pages.
About this book
High-Dimensional Statistics: A Non-Asymptotic Viewpoint by Martin J. Wainwright is a self-contained introduction to high-dimensional statistics aimed at the first-year graduate level. Cambridge University Press published this 568-page hardcover in 2019 as number 48 in the Cambridge Series in Statistical and Probabilistic Mathematics.
Chapters on core methodology and theory cover tail bounds, concentration inequalities, uniform laws and empirical processes, and random matrices. Other chapters explore particular model classes, including sparse linear models, matrix models with rank constraints, graphical models and non-parametric models. The book has hundreds of worked examples and exercises.
It is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning and related fields.
Product details
Science & Technology › Science & Nature
| Publisher | Cambridge University Press |
|---|---|
| Published | 2019 |
| Author | Martin J. Wainwright |
| Format | Hardcover, 568 pages |
| ISBN-13 | 978-1-108-49802-9 |
| ISBN-10 | 1108498027 |
| Size | 7.2 × 10.2 × 1.5 in · 2.7 lb |
| Condition | New |
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