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.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
