High Dimensional Probability II
High dimensional probability, in the sense that encompasses the topics rep resented in this volume, began about thirty years ago with research in two related areas: limit theorems for sums of independent Banach space valued random vectors and general Gaussian processes. An important feature in thes...
Other Authors: | , , |
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Format: | eBook |
Language: | English |
Published: |
Boston, MA
Birkhäuser
2000, 2000
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Edition: | 1st ed. 2000 |
Series: | Progress in Probability
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Subjects: | |
Online Access: | |
Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- Moment Bounds for Self-Normalized Martingales
- Exponential and Moment Inequalities for U-Statistics
- A Multiplicative Inequality for Concentration Functions of n-Fold Convolutions
- On Exact Maximal Khinchine Inequalities
- Strong Exponential Integrability of Martingales with Increments Bounded by a Sequence of Numbers
- On Uniform Laws of Large Numbers for Smoothed Empirical Measures
- Weak Convergence of Smoothed Empirical Processes: Beyond Donsker Classes
- Limit Theorems for Smoothed Empirical Processes
- Preservation Theorems for Glivenko-Cantelli and Uniform Glivenko-Cantelli Classes
- Continuité de certaines fonctions aléatoires gaussiennes à valeurs dans lp, 1?pof Cross Validation for Spline Smoothing
- Rademacher Processes and Bounding the Risk of Function Learning
- Bootstrapping Empirical Distributions under Auxiliary Information
- On the Characteristic Function of the Matrix von Mises-Fisher Distribution with Application to SO(N)—Deconvolution
- Testing for Ellipsoidal Symmetry of a Multivariate Distribution