Fundamentals of High-Dimensional Statistics

Fundamentals of High-Dimensional Statistics
Author :
Publisher : Springer Nature
Total Pages : 363
Release :
ISBN-10 : 9783030737924
ISBN-13 : 3030737926
Rating : 4/5 (926 Downloads)

Book Synopsis Fundamentals of High-Dimensional Statistics by : Johannes Lederer

Download or read book Fundamentals of High-Dimensional Statistics written by Johannes Lederer and published by Springer Nature. This book was released on 2021-11-16 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics. Each chapter is complemented by numerous exercises, many of them with detailed solutions, and computer labs in R that convey valuable practical insights. The book covers the theory and practice of high-dimensional linear regression, graphical models, and inference, ensuring readers have a smooth start in the field. It also offers suggestions for further reading. Given its scope, the textbook is intended for beginning graduate and advanced undergraduate students in statistics, biostatistics, and bioinformatics, though it will be equally useful to a broader audience.


Fundamentals of High-Dimensional Statistics Related Books

Fundamentals of High-Dimensional Statistics
Language: en
Pages: 363
Authors: Johannes Lederer
Categories: Mathematics
Type: BOOK - Published: 2021-11-16 - Publisher: Springer Nature

DOWNLOAD EBOOK

This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics. Each chapter is complemented by numerous exercise
Introduction to High-Dimensional Statistics
Language: en
Pages: 423
Authors: Christophe Giraud
Categories: Computers
Type: BOOK - Published: 2021-08-25 - Publisher: CRC Press

DOWNLOAD EBOOK

Praise for the first edition: "[This book] succeeds singularly at providing a structured introduction to this active field of research. ... it is arguably the m
Statistics for High-Dimensional Data
Language: en
Pages: 568
Authors: Peter Bühlmann
Categories: Mathematics
Type: BOOK - Published: 2011-06-08 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed ac
Mathematical Foundations of Infinite-Dimensional Statistical Models
Language: en
Pages: 706
Authors: Evarist Giné
Categories: Mathematics
Type: BOOK - Published: 2021-03-25 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

In nonparametric and high-dimensional statistical models, the classical Gauss–Fisher–Le Cam theory of the optimality of maximum likelihood estimators and Ba
High-Dimensional Probability
Language: en
Pages: 299
Authors: Roman Vershynin
Categories: Mathematics
Type: BOOK - Published: 2018-09-27 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in