High Dimensional Probability Ix

Author : Radosław Adamczak,Nathael Gozlan,Karim Lounici,Mokshay Madiman
Publisher : Springer Nature
Page : 445 pages
File Size : 50,7 Mb
Release : 2023-06-05
Category : Mathematics
ISBN : 9783031269790

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High Dimensional Probability IX by Radosław Adamczak,Nathael Gozlan,Karim Lounici,Mokshay Madiman Pdf

This volume collects selected papers from the Ninth High Dimensional Probability Conference, held virtually from June 15-19, 2020. These papers cover a wide range of topics and demonstrate how high-dimensional probability remains an active area of research with applications across many mathematical disciplines. Chapters are organized around four general topics: inequalities and convexity; limit theorems; stochastic processes; and high-dimensional statistics. High Dimensional Probability IX will be a valuable resource for researchers in this area.

Author : Christian Houdré,David M. Mason,Jan Rosiński,Jon A. Wellner
Publisher : Springer Science & Business Media
Page : 374 pages
File Size : 50,9 Mb
Release : 2013-04-19
Category : Mathematics
ISBN : 9783034804905

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High Dimensional Probability VI by Christian Houdré,David M. Mason,Jan Rosiński,Jon A. Wellner Pdf

This is a collection of papers by participants at High Dimensional Probability VI Meeting held from October 9-14, 2011 at the Banff International Research Station in Banff, Alberta, Canada. 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 areas of mathematics, statistics, and computer science. These include random matrix theory, nonparametric statistics, empirical process theory, statistical learning theory, concentration of measure phenomena, strong and weak approximations, distribution function estimation in high dimensions, combinatorial optimization, and random graph theory. The papers in this volume show that HDP theory continues to develop new tools, methods, techniques and perspectives to analyze the random phenomena. Both researchers and advanced students will find this book of great use for learning about new avenues of research.​

Author : Evarist Giné
Publisher : IMS
Page : 288 pages
File Size : 48,6 Mb
Release : 2006
Category : Mathematics
ISBN : 0940600676

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High Dimensional Probability by Evarist Giné Pdf

Author : Evarist Giné,David M. Mason,Jon A. Wellner
Publisher : Springer Science & Business Media
Page : 491 pages
File Size : 53,5 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461213581

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High Dimensional Probability II by Evarist Giné,David M. Mason,Jon A. Wellner Pdf

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 these past research studies has been the fact that they highlighted the es sential probabilistic nature of the problems considered. In part, this was because, by working on a general Banach space, one had to discard the extra, and often extraneous, structure imposed by random variables taking values in a Euclidean space, or by processes being indexed by sets in R or Rd. Doing this led to striking advances, particularly in Gaussian process theory. It also led to the creation or introduction of powerful new tools, such as randomization, decoupling, moment and exponential inequalities, chaining, isoperimetry and concentration of measure, which apply to areas well beyond those for which they were created. The general theory of em pirical processes, with its vast applications in statistics, the study of local times of Markov processes, certain problems in harmonic analysis, and the general theory of stochastic processes are just several of the broad areas in which Gaussian process techniques and techniques from probability in Banach spaces have made a substantial impact. Parallel to this work on probability in Banach spaces, classical proba bility and empirical process theory were enriched by the development of powerful results in strong approximations.

Author : Ernst Eberlein,Marjorie Hahn
Publisher : Birkhäuser
Page : 336 pages
File Size : 41,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9783034888295

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High Dimensional Probability by Ernst Eberlein,Marjorie Hahn Pdf

What is high dimensional probability? Under this broad name we collect topics with a common philosophy, where the idea of high dimension plays a key role, either in the problem or in the methods by which it is approached. Let us give a specific example that can be immediately understood, that of Gaussian processes. Roughly speaking, before 1970, the Gaussian processes that were studied were indexed by a subset of Euclidean space, mostly with dimension at most three. Assuming some regularity on the covariance, one tried to take advantage of the structure of the index set. Around 1970 it was understood, in particular by Dudley, Feldman, Gross, and Segal that a more abstract and intrinsic point of view was much more fruitful. The index set was no longer considered as a subset of Euclidean space, but simply as a metric space with the metric canonically induced by the process. This shift in perspective subsequently lead to a considerable clarification of many aspects of Gaussian process theory, and also to its applications in other settings.

Author : Roman Vershynin
Publisher : Cambridge University Press
Page : 299 pages
File Size : 42,6 Mb
Release : 2018-09-27
Category : Business & Economics
ISBN : 9781108415194

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High-Dimensional Probability by Roman Vershynin Pdf

An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

Author : Joergen Hoffmann-Joergensen,Michael B. Marcus,Jon A. Wellner
Publisher : Birkhäuser
Page : 346 pages
File Size : 53,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9783034880596

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High Dimensional Probability III by Joergen Hoffmann-Joergensen,Michael B. Marcus,Jon A. Wellner Pdf

The title High Dimensional Probability is used to describe the many tributaries of research on Gaussian processes and probability in Banach spaces that started in the early 1970s. Many of the problems that motivated researchers at that time were solved. But the powerful new tools created for their solution turned out to be applicable to other important areas of probability. They led to significant advances in the study of empirical processes and other topics in theoretical statistics and to a new approach to the study of aspects of Lévy processes and Markov processes in general. The papers in this book reflect these broad categories. The volume thus will be a valuable resource for postgraduates and reseachers in probability theory and mathematical statistics.

Author : Jørgen Hoffmann-Jørgensen,Michael B. Marcus,Jon A. Wellner
Publisher : Birkhauser
Page : 346 pages
File Size : 53,5 Mb
Release : 2003
Category : Mathematics
ISBN : 0817621873

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High Dimensional Probability III by Jørgen Hoffmann-Jørgensen,Michael B. Marcus,Jon A. Wellner Pdf

Author : Christian Houdré,David M. Mason,Patricia Reynaud-Bouret,Jan Rosiński
Publisher : Birkhäuser
Page : 480 pages
File Size : 42,8 Mb
Release : 2016-09-21
Category : Mathematics
ISBN : 9783319405193

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High Dimensional Probability VII by Christian Houdré,David M. Mason,Patricia Reynaud-Bouret,Jan Rosiński Pdf

This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Études Scientifiques de Cargèse (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 perspectives to analyze random phenomena.

Author : Nathael Gozlan,Rafał Latała,Karim Lounici,Mokshay Madiman
Publisher : Springer Nature
Page : 457 pages
File Size : 48,9 Mb
Release : 2019-11-26
Category : Mathematics
ISBN : 9783030263911

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High Dimensional Probability VIII by Nathael Gozlan,Rafał Latała,Karim Lounici,Mokshay Madiman Pdf

This volume collects selected papers from the 8th High Dimensional Probability meeting held at Casa Matemática Oaxaca (CMO), Mexico. 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, random graphs, information theory and convex geometry. The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena.

Author : Anonim
Publisher : Unknown
Page : 275 pages
File Size : 46,5 Mb
Release : 2006
Category : Electronic
ISBN : OCLC:1132151423

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High Dimensional Probability by Anonim Pdf

Author : Arnoldo Frigessi,Peter Bühlmann,Ingrid Glad,Mette Langaas,Sylvia Richardson,Marina Vannucci
Publisher : Springer
Page : 306 pages
File Size : 40,6 Mb
Release : 2016-02-16
Category : Mathematics
ISBN : 9783319270999

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Statistical Analysis for High-Dimensional Data by Arnoldo Frigessi,Peter Bühlmann,Ingrid Glad,Mette Langaas,Sylvia Richardson,Marina Vannucci Pdf

This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on future research directions, the contributions will benefit graduate students and researchers in computational biology, statistics and the machine learning community.

Author : David M. Mason
Publisher : Unknown
Page : 356 pages
File Size : 46,7 Mb
Release : 2009
Category : Gaussian processes
ISBN : 0940600781

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High Dimensional Probability V by David M. Mason Pdf

Author : Vladimir Spokoiny,Thorsten Dickhaus
Publisher : Springer
Page : 311 pages
File Size : 48,7 Mb
Release : 2014-10-25
Category : Mathematics
ISBN : 9783642399091

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Basics of Modern Mathematical Statistics by Vladimir Spokoiny,Thorsten Dickhaus Pdf

This textbook provides a unified and self-contained presentation of the main approaches to and ideas of mathematical statistics. It collects the basic mathematical ideas and tools needed as a basis for more serious study or even independent research in statistics. The majority of existing textbooks in mathematical statistics follow the classical asymptotic framework. Yet, as modern statistics has changed rapidly in recent years, new methods and approaches have appeared. The emphasis is on finite sample behavior, large parameter dimensions, and model misspecifications. The present book provides a fully self-contained introduction to the world of modern mathematical statistics, collecting the basic knowledge, concepts and findings needed for doing further research in the modern theoretical and applied statistics. This textbook is primarily intended for graduate and postdoc students and young researchers who are interested in modern statistical methods.

Author : Jin-Chuan Duan,Wolfgang Karl Härdle,James E. Gentle
Publisher : Springer Science & Business Media
Page : 804 pages
File Size : 44,8 Mb
Release : 2011-10-25
Category : Business & Economics
ISBN : 3642172547

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Handbook of Computational Finance by Jin-Chuan Duan,Wolfgang Karl Härdle,James E. Gentle Pdf

Any financial asset that is openly traded has a market price. Except for extreme market conditions, market price may be more or less than a “fair” value. Fair value is likely to be some complicated function of the current intrinsic value of tangible or intangible assets underlying the claim and our assessment of the characteristics of the underlying assets with respect to the expected rate of growth, future dividends, volatility, and other relevant market factors. Some of these factors that affect the price can be measured at the time of a transaction with reasonably high accuracy. Most factors, however, relate to expectations about the future and to subjective issues, such as current management, corporate policies and market environment, that could affect the future financial performance of the underlying assets. Models are thus needed to describe the stochastic factors and environment, and their implementations inevitably require computational finance tools.