High dimensional probability (268 Ergebnisse)

Hardcover. Zustand: Très bon. Ancien livre de bibliothèque avec équipements. Edition 1998. Tome 43. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 1998. Volume 43. Ammareal gives back up to 15% of this item's net price to charity organizations.…

Soft cover. Zustand: New. ISBN:9781009114295,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.

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Zustand: Brand New. New.SoftCover International edition. Different ISBN and Cover image but contents are same as US edition.Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

hardcover. Zustand: New. 2nd Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

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Hardcover. Zustand: Gut. 208 pp. Sun-bleached at the spine, name on endpaper, otherwise very well preserved copy 329 Sprache: Englisch Gewicht in Gramm: 568.

Hardcover. Zustand: Very Good. Zustand des Schutzumschlags: No Dust Jacket As Issued. Lightly crimped corner, clear plastic coating peeling from cover in a few places, otherwise text clean and tight; no dust jacket; Progress In Probability, 66; 8vo 8" - 9" tall; 387 pages.

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingModern portfolio construction operates in a high-dimensional regime where the number of assets routinely approaches or exceeds the number of observations. Classical covariance estimators break down in this setting, producing unreliable risk forecasts, distorted principal components, and unstable optimization results.This book develops the mathematical and computational framework needed to address these failures. It presents free probability and random matrix theory as practical tools for spectral analysis, covariance estimation, and risk modeling of large portfolios. Readers move from the Marchenko-Pastur law and free convolution to concrete procedures for cleaning empirical spectra, recovering population eigenvalues, and constructing robust risk measures under realistic market conditions.Core topics include: - Spectral methods for high-dimensional covariance matrices- Free deconvolution and eigenvalue cleaning techniques- Bias-corrected estimators for portfolio risk and factor models- Applications to covariance shrinkage, principal component analysis, and stress testing- Numerical implementation considerations for realistic asset universesThe material is self-contained yet rigorous, bridging theoretical results with the requirements of quantitative portfolio management. It is written for researchers, quant developers, and advanced practitioners who need reliable tools when classical multivariate statistics no longer apply.Vincent Bisette provides a focused treatment of free probability and random matrix methods tailored to the specific challenges of large-scale financial risk modeling.…

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Hardcover. Zustand: Sehr gut. 300 pp. Very well preserved copy 326 Sprache: Englisch Gewicht in Gramm: 711.

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Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.…

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Hardback. Zustand: New. 2nd. 'High-Dimensional Probability,' winner of the 2019 PROSE Award in Mathematics, offers an accessible and friendly introduction to key probabilistic methods for mathematical data scientists. Streamlined and updated, this second edition integrates theory, core tools, and modern applications. Concentration inequalities are central, including classical results like Hoeffding's and Chernoff's inequalities, and modern ones like the matrix Bernstein inequality. The book also develops methods based on stochastic processes - Slepian's, Sudakov's, and Dudley's inequalities, generic chaining, and VC-based bounds. Applications include covariance estimation, clustering, networks, semidefinite programming, coding, dimension reduction, matrix completion, and machine learning. New to this edition are 200 additional exercises, alongside extra hints to assist with self-study. Material on analysis, probability, and linear algebra has been reworked and expanded to help bridge the gap from a typical undergraduate background to a second course in probability.…

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Zustand: New. 2018. 1st Edition. hardcover. . . . . .

hardcover. Zustand: Sehr gut. 387 Seiten; 9783034804899.2 Gewicht in Gramm: 1.