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Fundamentals of High-Dimensional Statistics
With Exercises and R Labs
Taschenbuch von Johannes Lederer
Sprache: Englisch

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Beschreibung
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.
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.
Über den Autor

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.

Zusammenfassung

Introduces readers to the mathematical tools and principles of high-dimensional statistics

Includes numerous exercises, many of them with detailed solutions

Features computer labs in R that convey valuable practical insights

Offers suggestions for further reading

Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: 2022
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 372
Reihe: Springer Texts in Statistics
Inhalt: xiv
355 S.
13 s/w Illustr.
21 farbige Illustr.
355 p. 34 illus.
21 illus. in color.
ISBN-13: 9783030737948
ISBN-10: 3030737942
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Lederer, Johannes
Auflage: 2022
Hersteller: Springer International Publishing
Springer Texts in Statistics
Maße: 235 x 155 x 21 mm
Von/Mit: Johannes Lederer
Erscheinungsdatum: 18.11.2022
Gewicht: 0,563 kg
preigu-id: 125731221
Über den Autor

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.

Zusammenfassung

Introduces readers to the mathematical tools and principles of high-dimensional statistics

Includes numerous exercises, many of them with detailed solutions

Features computer labs in R that convey valuable practical insights

Offers suggestions for further reading

Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: 2022
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 372
Reihe: Springer Texts in Statistics
Inhalt: xiv
355 S.
13 s/w Illustr.
21 farbige Illustr.
355 p. 34 illus.
21 illus. in color.
ISBN-13: 9783030737948
ISBN-10: 3030737942
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Lederer, Johannes
Auflage: 2022
Hersteller: Springer International Publishing
Springer Texts in Statistics
Maße: 235 x 155 x 21 mm
Von/Mit: Johannes Lederer
Erscheinungsdatum: 18.11.2022
Gewicht: 0,563 kg
preigu-id: 125731221
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