Evarist Gine, Richard Nickl (University of Cambridge)

Mathematical Foundations of Infinite-Dimensional Statistical Models

• Broschiertes Buch

Produktbeschreibung

High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus on function estimation problems arising from random samples or from Gaussian regression/signal in white noise problems.

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Cambridge Series in Statistical and Probabilistic Mathematics
• Verlag: Cambridge University Press
• Revised ed
• Seitenzahl: 704
• Erscheinungstermin: 25. März 2021
• Englisch
• Abmessung: 252mm x 174mm x 48mm
• Gewicht: 1278g
• ISBN-13: 9781108994132
• ISBN-10: 110899413X
• Artikelnr.: 60914630

Autorenporträt

Evarist Giné (1944-2015) was Head of the Department of Mathematics at the University of Connecticut. Giné was a distinguished mathematician who worked on mathematical statistics and probability in infinite dimensions. He was the author of two books and more than 100 articles.

Inhaltsangabe

Preface
1. Nonparametric statistical models
2. Gaussian processes
3. Empirical processes
4. Function spaces and approximation theory
5. Linear nonparametric estimators
6. The minimax paradigm
7. Likelihood-based procedures
8. Adaptive inference
References
Author Index
Index.