Title
HighDimensional Statistics: A NonAsymptotic Viewpoint (Cambridge Series in Statistical and Probabilistic Mathematics, Series N,Used
Sold by Ergodebooks, an authorized reseller.
Returns accepted within 30 days | support@ergodebooks.com
Shipping Information
- Free Standard Shipping — United States only
- Processing Time: 1–3 business days
- Estimated Delivery: 3–5 business days after dispatch
- Double-boxed, fully insured & discreetly packaged
- Tracking number sent via email once dispatched
- Orders over $250 require signature upon delivery. Taxes calculated at checkout.
Returns & Refund
Returns accepted within 30 days of delivery.
Damaged or Defective Item
Free return shipping + replacement or full refund
Wrong Item Received
Free return shipping + replacement or full refund
Change of Mind
Return shipping at customer's expense · 25% restocking fee applies
Payment Option
Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a selfcontained introduction to the area of highdimensional statistics, aimed at the firstyear graduate level. It includes chapters that are focused on core methodology and theory including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices as well as chapters devoted to indepth exploration of particular model classes including sparse linear models, matrix models with rank constraints, graphical models, and various types of nonparametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for selfstudy by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and adapt modern statistical methods suited to largescale data.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.