An Introduction to Geometrical Probability

An Introduction to Geometrical Probability PDF Author: A.M. Mathai
Publisher: CRC Press
ISBN: 9789056996819
Category : Mathematics
Languages : en
Pages : 580

Get Book Here

Book Description
A useful guide for researchers and professionals, graduate and senior undergraduate students, this book provides an in-depth look at applied and geometrical probability with an emphasis on statistical distributions. A meticulous treatment of geometrical probability, kept at a level to appeal to a wider audience including applied researchers who will find the book to be both functional and practical with the large number of problems chosen from different disciplines A few topics such as packing and covering problems that have a vast literature are introduced here at a peripheral level for the purpose of familiarizing readers who are new to the area of research.

An Introduction to Geometrical Probability

An Introduction to Geometrical Probability PDF Author: A.M. Mathai
Publisher: CRC Press
ISBN: 9789056996819
Category : Mathematics
Languages : en
Pages : 580

Get Book Here

Book Description
A useful guide for researchers and professionals, graduate and senior undergraduate students, this book provides an in-depth look at applied and geometrical probability with an emphasis on statistical distributions. A meticulous treatment of geometrical probability, kept at a level to appeal to a wider audience including applied researchers who will find the book to be both functional and practical with the large number of problems chosen from different disciplines A few topics such as packing and covering problems that have a vast literature are introduced here at a peripheral level for the purpose of familiarizing readers who are new to the area of research.

Introduction to Geometric Probability

Introduction to Geometric Probability PDF Author: Daniel A. Klain
Publisher: Cambridge University Press
ISBN: 9780521596541
Category : Mathematics
Languages : en
Pages : 196

Get Book Here

Book Description
The purpose of this book is to present the three basic ideas of geometrical probability, also known as integral geometry, in their natural framework. In this way, the relationship between the subject and enumerative combinatorics is more transparent, and the analogies can be more productively understood. The first of the three ideas is invariant measures on polyconvex sets. The authors then prove the fundamental lemma of integral geometry, namely the kinematic formula. Finally the analogues between invariant measures and finite partially ordered sets are investigated, yielding insights into Hecke algebras, Schubert varieties and the quantum world, as viewed by mathematicians. Geometers and combinatorialists will find this a most stimulating and fruitful story.

Geometric Modeling in Probability and Statistics

Geometric Modeling in Probability and Statistics PDF Author: Ovidiu Calin
Publisher: Springer
ISBN: 3319077791
Category : Mathematics
Languages : en
Pages : 389

Get Book Here

Book Description
This book covers topics of Informational Geometry, a field which deals with the differential geometric study of the manifold probability density functions. This is a field that is increasingly attracting the interest of researchers from many different areas of science, including mathematics, statistics, geometry, computer science, signal processing, physics and neuroscience. It is the authors’ hope that the present book will be a valuable reference for researchers and graduate students in one of the aforementioned fields. This textbook is a unified presentation of differential geometry and probability theory, and constitutes a text for a course directed at graduate or advanced undergraduate students interested in applications of differential geometry in probability and statistics. The book contains over 100 proposed exercises meant to help students deepen their understanding, and it is accompanied by software that is able to provide numerical computations of several information geometric objects. The reader will understand a flourishing field of mathematics in which very few books have been written so far.

Geometric Aspects of Probability Theory and Mathematical Statistics

Geometric Aspects of Probability Theory and Mathematical Statistics PDF Author: V.V. Buldygin
Publisher: Springer Science & Business Media
ISBN: 9780792364139
Category : Mathematics
Languages : en
Pages : 322

Get Book Here

Book Description
This book demonstrates the usefulness of geometric methods in probability theory and mathematical statistics, and shows close relationships between these disciplines and convex analysis. Deep facts and statements from the theory of convex sets are discussed with their applications to various questions arising in probability theory, mathematical statistics, and the theory of stochastic processes. The book is essentially self-contained, and the presentation of material is thorough in detail. Audience: The topics considered in the book are accessible to a wide audience of mathematicians, and graduate and postgraduate students, whose interests lie in probability theory and convex geometry.

Geometric Probability

Geometric Probability PDF Author: Herbert Solomon
Publisher: SIAM
ISBN: 0898710251
Category : Mathematics
Languages : en
Pages : 180

Get Book Here

Book Description
Topics include: ways modern statistical procedures can yield estimates of pi more precisely than the original Buffon procedure traditionally used; the question of density and measure for random geometric elements that leave probability and expectation statements invariant under translation and rotation; and much more.

An Introduction to Mathematical Probability (Classic Reprint)

An Introduction to Mathematical Probability (Classic Reprint) PDF Author: Julian Lowell Coolidge
Publisher: Forgotten Books
ISBN: 9780331462692
Category : Mathematics
Languages : en
Pages : 236

Get Book Here

Book Description
Excerpt from An Introduction to Mathematical Probability The subjects of mean value and expectation, which have always played a central role in the theory of probabilities, have taken on additional importance in recent years, owing to the idea of dispersion, and its application to statistical series. For that reason they have been given a good deal of prominence. Per contra, geometrical probability, which is little more than a plaything, and the probability of causes, which rests on very shaky foundations, are treated briefly. Yet they should not be omitted entirely, for the former is related to statistical mechanics, and the latter gives the only answers we have to certain questions which recur insistently. The most important part of the theory is that which deals with the distribution of errors of observation. The funda mental question here is what to do with the exponential law of Gauss. I have tried to make it as plausible as I could by basing it, on very broad assumptions, even though this adds somewhat to the length of the deduction. I have, however, given the principles of combining observations as far as possible independently of the Gaussian law. The study of errors in two dimensions, which formerly interested few but students of artillery practice, has taken on a new importance through its relation to statistical correlation. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

Introduction to Probability

Introduction to Probability PDF Author: David F. Anderson
Publisher: Cambridge University Press
ISBN: 110824498X
Category : Mathematics
Languages : en
Pages : 447

Get Book Here

Book Description
This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

High-Dimensional Probability

High-Dimensional Probability PDF Author: Roman Vershynin
Publisher: Cambridge University Press
ISBN: 1108415199
Category : Business & Economics
Languages : en
Pages : 299

Get Book Here

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

Information Geometry and Its Applications

Information Geometry and Its Applications PDF Author: Shun-ichi Amari
Publisher: Springer
ISBN: 4431559787
Category : Mathematics
Languages : en
Pages : 378

Get Book Here

Book Description
This is the first comprehensive book on information geometry, written by the founder of the field. It begins with an elementary introduction to dualistic geometry and proceeds to a wide range of applications, covering information science, engineering, and neuroscience. It consists of four parts, which on the whole can be read independently. A manifold with a divergence function is first introduced, leading directly to dualistic structure, the heart of information geometry. This part (Part I) can be apprehended without any knowledge of differential geometry. An intuitive explanation of modern differential geometry then follows in Part II, although the book is for the most part understandable without modern differential geometry. Information geometry of statistical inference, including time series analysis and semiparametric estimation (the Neyman–Scott problem), is demonstrated concisely in Part III. Applications addressed in Part IV include hot current topics in machine learning, signal processing, optimization, and neural networks. The book is interdisciplinary, connecting mathematics, information sciences, physics, and neurosciences, inviting readers to a new world of information and geometry. This book is highly recommended to graduate students and researchers who seek new mathematical methods and tools useful in their own fields.

Introduction to Counting and Probability

Introduction to Counting and Probability PDF Author: David Patrick
Publisher:
ISBN: 9781934124109
Category : Counting
Languages : en
Pages : 0

Get Book Here

Book Description