{"product_id":"9783030800642","title":"High-Dimensional Covariance Matrix Estimation : An Introduction to Random Matrix Theory by Aygul Zagidullina","description":"This book presents covariance matrix estimation and related aspects of random matrix theory. It focuses on the sample covariance matrix estimator and provides a holistic description of its properties under two asymptotic regimes: the traditional one, and the high-dimensional regime that better fits the big data context. It draws attention to the deficiencies of standard statistical tools when used in the high-dimensional setting, and introduces the basic concepts and major results related to spectral statistics and random matrix theory under high-dimensional asymptotics in an understandable and reader-friendly way. The aim of this book is to inspire applied statisticians, econometricians, and machine learning practitioners who analyze high-dimensional data to apply the recent developments in their work.\u003cbr\u003eBinding: Paperback \/ softback","brand":"Gardners","offers":[{"title":"Default Title","offer_id":56310341632373,"sku":"9783030800642","price":59.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0612\/7193\/3106\/files\/9783030800642.jpg?v=1762814702","url":"https:\/\/backstory.london\/products\/9783030800642","provider":"Backstory","version":"1.0","type":"link"}