Fundamentals of High-Dimensional Statistics - Johannes Lederer

Fundamentals of High-Dimensional Statistics

With Exercises and R Labs
Buch | Softcover
XIV, 355 Seiten
2022 | 2022
Springer International Publishing (Verlag)
978-3-030-73794-8 (ISBN)
85,59 inkl. MwSt
This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics. 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.

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.

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.

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. 

Erscheinungsdatum
Reihe/Serie Springer Texts in Statistics
Zusatzinfo XIV, 355 p. 34 illus., 21 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 563 g
Themenwelt Mathematik / Informatik Informatik Datenbanken
Informatik Theorie / Studium Algorithmen
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Schlagworte Calibration • estimation • exercises and solutions • Graphical Models • high-dimensional data • high-dimensional inference • High-Dimensional Statistics • Lasso • linear regression • Prediction • Regularization • R labs • sparsity • Statistical Inference
ISBN-10 3-030-73794-2 / 3030737942
ISBN-13 978-3-030-73794-8 / 9783030737948
Zustand Neuware
Haben Sie eine Frage zum Produkt?
Mehr entdecken
aus dem Bereich
IT zum Anfassen für alle von 9 bis 99 – vom Navi bis Social Media

von Jens Gallenbacher

Buch | Softcover (2021)
Springer (Verlag)
29,99
Interlingua zur Gewährleistung semantischer Interoperabilität in der …

von Josef Ingenerf; Cora Drenkhahn

Buch | Softcover (2023)
Springer Fachmedien (Verlag)
32,99