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E-grāmata: High Dimensional Probability VII: The Cargese Volume

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  • Formāts: PDF+DRM
  • Sērija : Progress in Probability 71
  • Izdošanas datums: 21-Sep-2016
  • Izdevniecība: Birkhauser Verlag AG
  • Valoda: eng
  • ISBN-13: 9783319405193
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  • Formāts: PDF+DRM
  • Sērija : Progress in Probability 71
  • Izdošanas datums: 21-Sep-2016
  • Izdevniecība: Birkhauser Verlag AG
  • Valoda: eng
  • ISBN-13: 9783319405193

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This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d"Études Scientifiques de Cargčse (IESC) in Corsica, France.High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs.The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspecti

ves to analyze random phenomena.

Dedication to Evarist Gine-Masdeu.- Inequalities and Convexity.- Limit Theorems.- Stochastic Processes.- High Dimensional Statistics.
Part I Inequalities and Convexity
Stability of Cramer's Characterization of Normal Laws in Information Distances
3(34)
Sergey Bobkov
Gennadiy Chistyakov
Friedrich Gotze
V.N. Sudakov's Work on Expected Suprema of Gaussian Processes
37(8)
Richard M. Dudley
Optimal Concentration of Information Content for Log-Concave Densities
45(16)
Matthieu Fradelizi
Mokshay Madiman
Liyao Wang
Maximal Inequalities for Dependent Random Variables
61(44)
Jørgen Hoffmann-Jørgensen
On the Order of the Central Moments of the Length of the Longest Common Subsequences in Random Words
105(32)
Christian Houdre
Jinyong Ma
A Weighted Approximation Approach to the Study of the Empirical Wasserstein Distance
137(18)
David M. Mason
On the Product of Random Variables and Moments of Sums Under Dependence
155(18)
Magda Peligrad
The Expected Norm of a Sum of Independent Random Matrices: An Elementary Approach
173(30)
Joel A. Tropp
Fechner's Distribution and Connections to Skew Brownian Motion
203(16)
Jon A. Wellner
Part II Limit Theorems
Erdos-Renyi-Type Functional Limit Laws for Renewal Processes
219(36)
Paul Deheuvels
Joseph G. Steinebach
Limit Theorems for Quantile and Depth Regions for Stochastic Processes
255(26)
James Kuelbs
Joel Zinn
In Memory of Wenbo V. Li's Contributions
281(14)
Qi-Man Shao
Part III Stochastic Processes
Orlicz Integrability of Additive Functionals of Harris Ergodic Markov Chains
295(32)
Radoslaw Adamczak
Witold Bednorz
Bounds for Stochastic Processes on Product Index Spaces
327(32)
Witold Bednorz
Permanental Vectors and Selfdecomposability
359(4)
Nathalie Eisenbaum
Permanental Random Variables, M-Matrices and α-Permanents
363(18)
Michael B. Marcus
Jay Rosen
Convergence in Law Implies Convergence in Total Variation for Polynomials in Independent Gaussian, Gamma or Beta Random Variables
381(16)
Ivan Nourdin
Guillaume Poly
Part IV High Dimensional Statistics
Perturbation of Linear Forms of Singular Vectors Under Gaussian Noise
397(28)
Vladimir Koltchinskii
Dong Xia
Optimal Kernel Selection for Density Estimation
425
Matthieu Lerasle
Nelo Molter Magalhaes
Patricia Reynaud-Bouret