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Book An Introduction to Geometrical Probability

Download or read book An Introduction to Geometrical Probability written by A.M. Mathai and published by CRC Press. This book was released on 1999-12-01 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Introduction to Geometric Probability

Download or read book Introduction to Geometric Probability written by Daniel A. Klain and published by Cambridge University Press. This book was released on 1997-12-11 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Geometric Modeling in Probability and Statistics

Download or read book Geometric Modeling in Probability and Statistics written by Ovidiu Calin and published by Springer. This book was released on 2014-07-17 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Geometric Probability

Download or read book Geometric Probability written by Herbert Solomon and published by SIAM. This book was released on 1978-06-01 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book High Dimensional Probability

Download or read book High Dimensional Probability written by Roman Vershynin and published by Cambridge University Press. This book was released on 2018-09-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

Book Introduction to Probability

Download or read book Introduction to Probability written by David F. Anderson and published by Cambridge University Press. This book was released on 2017-11-02 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book An Introduction to Mathematical Probability  Classic Reprint

Download or read book An Introduction to Mathematical Probability Classic Reprint written by Julian Lowell Coolidge and published by Forgotten Books. This book was released on 2017-11-19 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Information Geometry and Its Applications

Download or read book Information Geometry and Its Applications written by Shun-ichi Amari and published by Springer. This book was released on 2016-02-02 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Introduction to Probability

Download or read book Introduction to Probability written by Dimitri Bertsekas and published by Athena Scientific. This book was released on 2008-07-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intuitive, yet precise introduction to probability theory, stochastic processes, statistical inference, and probabilistic models used in science, engineering, economics, and related fields. This is the currently used textbook for an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students, and for a leading online class on the subject. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject. It also contains a number of more advanced topics, including transforms, sums of random variables, a fairly detailed introduction to Bernoulli, Poisson, and Markov processes, Bayesian inference, and an introduction to classical statistics. The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis is explained intuitively in the main text, and then developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems.

Book Introduction to Counting and Probability

Download or read book Introduction to Counting and Probability written by David Patrick and published by . This book was released on 2007-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Factorization Calculus and Geometric Probability

Download or read book Factorization Calculus and Geometric Probability written by R. V. Ambartzumian and published by Cambridge University Press. This book was released on 1990-09-28 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The classical subjects of geometric probability and integral geometry, and the more modern one of stochastic geometry, are developed here in a novel way to provide a framework in which they can be studied. The author focuses on factorization properties of measures and probabilities implied by the assumption of their invariance with respect to a group, in order to investigate nontrivial factors. The study of these properties is the central theme of the book. Basic facts about integral geometry and random point process theory are developed in a simple geometric way, so that the whole approach is suitable for a nonspecialist audience. Even in the later chapters, where the factorization principles are applied to geometrical processes, the only prerequisites are standard courses on probability and analysis. The main ideas presented have application to such areas as stereology and geometrical statistics and this book will be a useful reference book for university students studying probability theory and stochastic geometry, and research mathematicians interested in this area.

Book Differential Geometry and Statistics

Download or read book Differential Geometry and Statistics written by M.K. Murray and published by Routledge. This book was released on 2017-10-19 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several years ago our statistical friends and relations introduced us to the work of Amari and Barndorff-Nielsen on applications of differential geometry to statistics. This book has arisen because we believe that there is a deep relationship between statistics and differential geometry and moreoever that this relationship uses parts of differential geometry, particularly its 'higher-order' aspects not readily accessible to a statistical audience from the existing literature. It is, in part, a long reply to the frequent requests we have had for references on differential geometry! While we have not gone beyond the path-breaking work of Amari and Barndorff- Nielsen in the realm of applications, our book gives some new explanations of their ideas from a first principles point of view as far as geometry is concerned. In particular it seeks to explain why geometry should enter into parametric statistics, and how the theory of asymptotic expansions involves a form of higher-order differential geometry. The first chapter of the book explores exponential families as flat geometries. Indeed the whole notion of using log-likelihoods amounts to exploiting a particular form of flat space known as an affine geometry, in which straight lines and planes make sense, but lengths and angles are absent. We use these geometric ideas to introduce the notion of the second fundamental form of a family whose vanishing characterises precisely the exponential families.

Book An Introduction to Geometrical Physics

Download or read book An Introduction to Geometrical Physics written by Aldrovandi Ruben and published by World Scientific. This book was released on 2016-10-07 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the unifying power of the geometrical language in bringing together concepts from many different areas of physics, ranging from classical physics to the theories describing the four fundamental interactions of Nature -- gravitational, electromagnetic, strong nuclear, and weak nuclear. The book provides in a single volume a thorough introduction to topology and differential geometry, as well as many applications to both mathematical and physical problems. It is aimed as an elementary text and is intended for first year graduate students. In addition to the traditional contents of books on special and general relativities, this book discusses also some recent advances such as de Sitter invariant special relativity, teleparallel gravity and their implications in cosmology for those wishing to reach a higher level of understanding.

Book The Geometry of Uncertainty

Download or read book The Geometry of Uncertainty written by Fabio Cuzzolin and published by Springer Nature. This book was released on 2020-12-17 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: The principal aim of this book is to introduce to the widest possible audience an original view of belief calculus and uncertainty theory. In this geometric approach to uncertainty, uncertainty measures can be seen as points of a suitably complex geometric space, and manipulated in that space, for example, combined or conditioned. In the chapters in Part I, Theories of Uncertainty, the author offers an extensive recapitulation of the state of the art in the mathematics of uncertainty. This part of the book contains the most comprehensive summary to date of the whole of belief theory, with Chap. 4 outlining for the first time, and in a logical order, all the steps of the reasoning chain associated with modelling uncertainty using belief functions, in an attempt to provide a self-contained manual for the working scientist. In addition, the book proposes in Chap. 5 what is possibly the most detailed compendium available of all theories of uncertainty. Part II, The Geometry of Uncertainty, is the core of this book, as it introduces the author’s own geometric approach to uncertainty theory, starting with the geometry of belief functions: Chap. 7 studies the geometry of the space of belief functions, or belief space, both in terms of a simplex and in terms of its recursive bundle structure; Chap. 8 extends the analysis to Dempster’s rule of combination, introducing the notion of a conditional subspace and outlining a simple geometric construction for Dempster’s sum; Chap. 9 delves into the combinatorial properties of plausibility and commonality functions, as equivalent representations of the evidence carried by a belief function; then Chap. 10 starts extending the applicability of the geometric approach to other uncertainty measures, focusing in particular on possibility measures (consonant belief functions) and the related notion of a consistent belief function. The chapters in Part III, Geometric Interplays, are concerned with the interplay of uncertainty measures of different kinds, and the geometry of their relationship, with a particular focus on the approximation problem. Part IV, Geometric Reasoning, examines the application of the geometric approach to the various elements of the reasoning chain illustrated in Chap. 4, in particular conditioning and decision making. Part V concludes the book by outlining a future, complete statistical theory of random sets, future extensions of the geometric approach, and identifying high-impact applications to climate change, machine learning and artificial intelligence. The book is suitable for researchers in artificial intelligence, statistics, and applied science engaged with theories of uncertainty. The book is supported with the most comprehensive bibliography on belief and uncertainty theory.

Book Random Geometric Graphs

Download or read book Random Geometric Graphs written by Mathew Penrose and published by Oxford University Press. This book was released on 2003 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides and explains the mathematics behind geometric graph theory, which studies the properties of a graph that consists of nodes placed in Euclidean space so that edges can be added to connect points that are close to one another. For example, a collection of trees scattered in a forest and the disease that is passed between them, a set of nests of animals or birds on a region and the communication between them or communication between communications stations or nerve cells. Aimed at graduate students and researchers in probability, statistics, combinatorics and graph theory including computer scientists, it covers topics such as: technical tools, edge and component counts, vertex degrees, clique and chromatic number, and connectivity. Applications of this theory are used in the study of neural networks, spread of disease, astrophysics and spatial statistics.

Book Probability

    Book Details:
  • Author : John J. Kinney
  • Publisher : John Wiley & Sons
  • Release : 2015-01-13
  • ISBN : 111894710X
  • Pages : 480 pages

Download or read book Probability written by John J. Kinney and published by John Wiley & Sons. This book was released on 2015-01-13 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "This is a well-written and impressively presentedintroduction to probability and statistics. The text throughout ishighly readable, and the author makes liberal use of graphs anddiagrams to clarify the theory." - The Statistician Thoroughly updated, Probability: An Introduction withStatistical Applications, Second Edition features acomprehensive exploration of statistical data analysis as anapplication of probability. The new edition provides anintroduction to statistics with accessible coverage of reliability,acceptance sampling, confidence intervals, hypothesis testing, andsimple linear regression. Encouraging readers to develop a deeperintuitive understanding of probability, the author presentsillustrative geometrical presentations and arguments without theneed for rigorous mathematical proofs. The Second Edition features interesting and practicalexamples from a variety of engineering and scientific fields, aswell as: Over 880 problems at varying degrees of difficulty allowingreaders to take on more challenging problems as their skill levelsincrease Chapter-by-chapter projects that aid in the visualization ofprobability distributions New coverage of statistical quality control and qualityproduction An appendix dedicated to the use ofMathematica® and a companion website containing thereferenced data sets Featuring a practical and real-world approach, this textbook isideal for a first course in probability for students majoring instatistics, engineering, business, psychology, operations research,and mathematics. Probability: An Introduction with StatisticalApplications, Second Edition is also an excellent reference forresearchers and professionals in any discipline who need to makedecisions based on data as well as readers interested in learninghow to accomplish effective decision making from data.

Book New Foundations for Physical Geometry

Download or read book New Foundations for Physical Geometry written by Tim Maudlin and published by Oxford University Press. This book was released on 2014-02 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tim Maudlin sets out a completely new method for describing the geometrical structure of spaces, and thus a better mathematical tool for describing and understanding space-time. He presents a historical review of the development of geometry and topology, and then his original Theory of Linear Structures.