Introduction to High-Dimensional Statistics


Introduction to High-Dimensional Statistics
Authors: Christophe Giraud
Year: 2021
Publisher: Chapman and Hall/CRC
Language: English
ISBN 13: 9780367716226
ISBN 10: 367716224
Categories: Computers, Computer Science
Pages: 320 / 319
Edition: 2

Availability: 5000 in stock

SKU: 9780367716226 Categories: ,

Introduction to High-Dimensional Statistics Christophe Giraud
Praise for the first edition:”[This book] succeeds singularly at providing a structured introduction to this active field of research. … it is arguably the most accessible overview yet published of the mathematical ideas and principles that one needs to master to enter the field of high-dimensional statistics. … recommended to anyone interested in the main results of current research in high-dimensional statistics as well as anyone interested in acquiring the core mathematical skills to enter this area of research.”
―Journal of the American Statistical AssociationIntroduction to High-Dimensional Statistics, Second Edition preserves the philosophy of the first edition: to be a concise guide for students and researchers discovering the area and interested in the mathematics involved. The main concepts and ideas are presented in simple settings, avoiding thereby unessential technicalities. High-dimensional statistics is a fast-evolving field, and much progress has been made on a large variety of topics, providing new insights and methods. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this new edition: Offers revised chapters from the previous edition, with the inclusion of many additional materials on some important topics, including compress sensing, estimation with convex constraints, the slope estimator, simultaneously low-rank and row-sparse linear regression, or aggregation of a continuous set of estimators. Introduces three new chapters on iterative algorithms, clustering, and minimax lower bounds. Provides enhanced appendices, minimax lower-bounds mainly with the addition of the Davis-Kahan perturbation bound and of two simple versions of the Hanson-Wright concentration inequality. Covers cutting-edge statistical methods including model selection, sparsity and the Lasso, iterative hard thresholding, aggregation, support vector machines, and learning theory. Provides detailed exercises at the end of every chapter with collaborative solutions on a wiki site. Illustrates concepts with simple but clear practical examples. Categories:
Computers – Computer Science
Chapman and Hall/CRC
346 / 364
ISBN 10:
ISBN 13:
Chapman & Hall/CRC Monographs on Statistics and Applied Probability 168
99 MB


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Introduction to High-Dimensional Statistics

Availability: 5000 in stock