Fundamentals of High-Dimensional Statistics: With Exercises and R Labs

Author:   Johannes Lederer
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
ISBN:  

9783030737917


Pages:   355
Publication Date:   17 November 2021
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Fundamentals of High-Dimensional Statistics: With Exercises and R Labs


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Overview

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.

Full Product Details

Author:   Johannes Lederer
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
Weight:   0.812kg
ISBN:  

9783030737917


ISBN 10:   3030737918
Pages:   355
Publication Date:   17 November 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Preface.- Notation.- Introduction.- Linear Regression.- Graphical Models.- Tuning-Parameter Calibration.- Inference.- Theory I: Prediction.- Theory II: Estimation and Support Recovery.- A Solutions.- B Mathematical Background.- Bibliography.- Index. 

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Author Information

Johannes Lederer is a Professor of Statistics at the Ruhr-University Bochum, Germany. He received his PhD in mathematics from the ETH Zürich and subsequently held positions at UC Berkeley, Cornell University, and the University of Washington. He has taught high-dimensional statistics to applied and mathematical audiences alike, e.g. as a Visiting Professor at the Institute of Statistics, Biostatistics, and Actuarial Sciences at UC Louvain, and at the University of Hong Kong Business School.

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