Theory of Stochastic Objects

Probability, Stochastic Processes and Inference

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Author: Athanasios Christou Micheas

Publisher: CRC Press

ISBN: 1466515228

Category: Mathematics

Page: 378

View: 8238

This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks; one would need material on real analysis, measure and probability theory, as well as stochastic processes - in addition to at least one text on statistics- to capture the detail and depth of material that has gone into this volume. Presents and illustrates ‘random objects’ in different contexts, under a unified framework, starting with rudimentary results on random variables and random sequences, all the way up to stochastic partial differential equations. Reviews rudimentary probability and introduces statistical inference, from basic to advanced, thus making the transition from basic statistical modeling and estimation to advanced topics more natural and concrete. Compact and comprehensive presentation of the material that will be useful to a reader from the mathematics and statistical sciences, at any stage of their career, either as a graduate student, an instructor, or an academician conducting research and requiring quick references and examples to classic topics. Includes 378 exercises, with the solutions manual available on the book's website. 121 illustrative examples of the concepts presented in the text (many including multiple items in a single example). The book is targeted towards students at the master’s and Ph.D. levels, as well as, academicians in the mathematics, statistics and related disciplines. Basic knowledge of calculus and matrix algebra is required. Prior knowledge of probability or measure theory is welcomed but not necessary.

Stochastic Geometry

Selected Topics

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Author: Viktor Beneš,Jan Rataj

Publisher: Springer

ISBN: 3030135470

Category: Stochastic geometry

Page: 221

View: 4083

Stable Non-Gaussian Self-Similar Processes with Stationary Increments

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Author: Vladas Pipiras,Murad S. Taqqu

Publisher: Springer

ISBN: 3319623311

Category: Mathematics

Page: 135

View: 730

This book provides a self-contained presentation on the structure of a large class of stable processes, known as self-similar mixed moving averages. The authors present a way to describe and classify these processes by relating them to so-called deterministic flows. The first sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed moving averages and self-similarity. In-depth appendices are also included. This book is aimed at graduate students and researchers working in probability theory and statistics.

Stochastic Processes

From Applications to Theory

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Author: Pierre Del Moral,Spiridon Penev

Publisher: CRC Press

ISBN: 1498701841

Category: Mathematics

Page: 866

View: 3929

Unlike traditional books presenting stochastic processes in an academic way, this book includes concrete applications that students will find interesting such as gambling, finance, physics, signal processing, statistics, fractals, and biology. Written with an important illustrated guide in the beginning, it contains many illustrations, photos and pictures, along with several website links. Computational tools such as simulation and Monte Carlo methods are included as well as complete toolboxes for both traditional and new computational techniques.

Long-Range Dependence and Self-Similarity

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Author: Vladas Pipiras,Murad S. Taqqu

Publisher: Cambridge University Press

ISBN: 1108210198

Category: Mathematics

Page: N.A

View: 2043

This modern and comprehensive guide to long-range dependence and self-similarity starts with rigorous coverage of the basics, then moves on to cover more specialized, up-to-date topics central to current research. These topics concern, but are not limited to, physical models that give rise to long-range dependence and self-similarity; central and non-central limit theorems for long-range dependent series, and the limiting Hermite processes; fractional Brownian motion and its stochastic calculus; several celebrated decompositions of fractional Brownian motion; multidimensional models for long-range dependence and self-similarity; and maximum likelihood estimation methods for long-range dependent time series. Designed for graduate students and researchers, each chapter of the book is supplemented by numerous exercises, some designed to test the reader's understanding, while others invite the reader to consider some of the open research problems in the field today.

Stochastic Processes

An Introduction, Third Edition

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Author: Peter Watts Jones,Peter Smith

Publisher: CRC Press

ISBN: 1498778127

Category: Mathematics

Page: 255

View: 3114

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with a review of relevant fundamental probability. It then covers gambling problems, random walks, and Markov chains. The authors go on to discuss random processes continuous in time, including Poisson, birth and death processes, and general population models, and present an extended discussion on the analysis of associated stationary processes in queues. The book also explores reliability and other random processes, such as branching, martingales, and simple epidemics. A new chapter describing Brownian motion, where the outcomes are continuously observed over continuous time, is included. Further applications, worked examples and problems, and biographical details have been added to this edition. Much of the text has been reworked. The appendix contains key results in probability for reference. This concise, updated book makes the material accessible, highlighting simple applications and examples. A solutions manual with fully worked answers of all end-of-chapter problems, and Mathematica® and R programs illustrating many processes discussed in the book, can be downloaded from crcpress.com.

Stationary Stochastic Processes

Theory and Applications

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Author: Georg Lindgren

Publisher: CRC Press

ISBN: 1466557796

Category: Mathematics

Page: 375

View: 798

Intended for a second course in stationary processes, Stationary Stochastic Processes: Theory and Applications presents the theory behind the field’s widely scattered applications in engineering and science. In addition, it reviews sample function properties and spectral representations for stationary processes and fields, including a portion on stationary point processes. Features Presents and illustrates the fundamental correlation and spectral methods for stochastic processes and random fields Explains how the basic theory is used in special applications like detection theory and signal processing, spatial statistics, and reliability Motivates mathematical theory from a statistical model-building viewpoint Introduces a selection of special topics, including extreme value theory, filter theory, long-range dependence, and point processes Provides more than 100 exercises with hints to solutions and selected full solutions This book covers key topics such as ergodicity, crossing problems, and extremes, and opens the doors to a selection of special topics, like extreme value theory, filter theory, long-range dependence, and point processes, and includes many exercises and examples to illustrate the theory. Precise in mathematical details without being pedantic, Stationary Stochastic Processes: Theory and Applications is for the student with some experience with stochastic processes and a desire for deeper understanding without getting bogged down in abstract mathematics.

Modeling and Analysis of Stochastic Systems, Third Edition

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Author: Vidyadhar G. Kulkarni

Publisher: CRC Press

ISBN: 1498756727

Category: Business & Economics

Page: 606

View: 3222

Building on the author’s more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. The third edition has been updated with several new applications, including the Google search algorithm in discrete time Markov chains, several examples from health care and finance in continuous time Markov chains, and square root staffing rule in Queuing models. More than 50 new exercises have been added to enhance its use as a course text or for self-study. The sequence of chapters and exercises has been maintained between editions, to enable those now teaching from the second edition to use the third edition. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, readers will be well-equipped to build and analyze useful stochastic models for real-life situations.

Stochastic Modeling of Scientific Data

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Author: Peter Guttorp,Vladimir N. Minin

Publisher: CRC Press

ISBN: 1351413651

Category: Mathematics

Page: 384

View: 3581

Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner. The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises. Markov chain Monte Carlo methods are introduced for evaluating likelihoods in complicated models and the forward backward algorithm for analyzing hidden Markov models is presented. The strength of this text lies in the use of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes and their statistical inference puts it in a new category of probability textbooks. The numerous examples and exercises are drawn from astronomy, geology, genetics, hydrology, neurophysiology and physics.

Mathematische Statistik

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Author: Claudia Czado,Thorsten Schmidt

Publisher: Springer-Verlag

ISBN: 364217261X

Category: Mathematics

Page: 280

View: 3247

Das Buch liefert einen Überblick über die Theorie statistischer Schätz- und Testverfahren. Die Autoren bieten eine verständliche und praxisorientierte Schritt-für-Schritt Einführung in die mathematischen Methoden der Statistik. Um Lesern den Einstieg in die Materie zu erleichtern, präsentieren sie elementare Beweise ohne maßtheoretische Hilfsmittel und bieten viele ausgearbeitete Anwendungsbeispiele. Anhand einer umfangreichen Aufgabensammlung am Ende jedes Kapitels können Leser ihren Lernfortschritt überprüfen.

Modeling and Analysis of Stochastic Systems

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Author: Vidyadhar G. Kulkarni

Publisher: CRC Press

ISBN: 149875662X

Category: Business & Economics

Page: 584

View: 3951

Building on the author’s more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. The third edition has been updated with several new applications, including the Google search algorithm in discrete time Markov chains, several examples from health care and finance in continuous time Markov chains, and square root staffing rule in Queuing models. More than 50 new exercises have been added to enhance its use as a course text or for self-study. The sequence of chapters and exercises has been maintained between editions, to enable those now teaching from the second edition to use the third edition. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, readers will be well-equipped to build and analyze useful stochastic models for real-life situations.

Theory and Modeling of Stochastic Objects

Point Processes to Random Sets

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Author: Athanasios Christou Micheas

Publisher: Chapman and Hall/CRC

ISBN: 9781466515208

Category: Mathematics

Page: 416

View: 9761

This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks. One would need to use one book on Real Analysis, one on Measure and/or Probability theory, one in Stochastic processes, and at least one on Statistics to capture the detail and depth of material that has gone into this text. The book is targeted towards students at the master's and Ph.D. levels, as well as, academicians in the mathematics, statistics and related disciplines. Basic knowledge of calculus and matrix algebra is required. Prior knowledge of probability or measure theory is welcomed but not necessary.

Elementare Wahrscheinlichkeitstheorie und stochastische Prozesse

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Author: Kai L. Chung

Publisher: Springer-Verlag

ISBN: 3642670334

Category: Mathematics

Page: 346

View: 3222

Aus den Besprechungen: "Unter den zahlreichen Einführungen in die Wahrscheinlichkeitsrechnung bildet dieses Buch eine erfreuliche Ausnahme. Der Stil einer lebendigen Vorlesung ist über Niederschrift und Übersetzung hinweg erhalten geblieben. In jedes Kapitel wird sehr anschaulich eingeführt. Sinn und Nützlichkeit der mathematischen Formulierungen werden den Lesern nahegebracht. Die wichtigsten Zusammenhänge sind als mathematische Sätze klar formuliert." #FREQUENZ#1

Modeling and Analysis of Stochastic Systems, Second Edition

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Author: Vidyadhar G. Kulkarni

Publisher: Chapman and Hall/CRC

ISBN: 9781439808757

Category: Business & Economics

Page: 544

View: 2921

Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edition: a new chapter on diffusion processes that gives an accessible and non-measure-theoretic treatment with applications to finance; a more streamlined, application-oriented approach to renewal, regenerative, and Markov regenerative processes; and, two appendices that collect relevant results from analysis and differential and difference equations. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, students will be well-equipped to build and analyze useful stochastic models for various situations. A collection of MATLAB[registered]-based programs can be downloaded from the author's website and a solutions manual is available for qualifying instructors.

Stochastic Processes with Applications to Finance

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Author: Masaaki Kijima

Publisher: CRC Press

ISBN: 9781584882244

Category: Mathematics

Page: 288

View: 6239

In recent years, modeling financial uncertainty using stochastic processes has become increasingly important, but it is commonly perceived as requiring a deep mathematical background. Stochastic Processes with Applications to Finance shows that this is not necessarily so. It presents the theory of discrete stochastic processes and their applications in finance in an accessible treatment that strikes a balance between the abstract and the practical. Using an approach that views sophisticated stochastic calculus as based on a simple class of discrete processes-"random walks"-the author first provides an elementary introduction to the relevant areas of real analysis and probability. He then uses random walks to explain the change of measure formula, the reflection principle, and the Kolmogorov backward equation. The Black-Scholes formula is derived as a limit of binomial model, and applications to the pricing of derivative securities are presented. Another primary focus of the book is the pricing of corporate bonds and credit derivatives, which the author explains in terms of discrete default models. By presenting important results in discrete processes and showing how to transfer those results to their continuous counterparts, Stochastic Processes with Applications to Finance imparts an intuitive and practical understanding of the subject. This unique treatment is ideal both as a text for a graduate-level class and as a reference for researchers and practitioners in financial engineering, operations research, and mathematical and statistical finance.

Stochastic Processes with Applications to Finance, Second Edition

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Author: Masaaki Kijima

Publisher: CRC Press

ISBN: 143988482X

Category: Business & Economics

Page: 343

View: 4369

Financial engineering has been proven to be a useful tool for risk management, but using the theory in practice requires a thorough understanding of the risks and ethical standards involved. Stochastic Processes with Applications to Finance, Second Edition presents the mathematical theory of financial engineering using only basic mathematical tools that are easy to understand even for those with little mathematical expertise. This second edition covers several important developments in the financial industry. New to the Second Edition A chapter on the change of measures and pricing of insurance products Many examples of the change of measure technique, including its use in asset pricing theory A section on the use of copulas, especially in the pricing of CDOs Two chapters that offer more coverage of interest rate derivatives and credit derivatives Exploring the merge of actuarial science and financial engineering, this edition examines how the pricing of insurance products, such as equity-linked annuities, requires knowledge of asset pricing theory since the equity index can be traded in the market. The book looks at the development of many probability transforms for pricing insurance risks, including the Esscher transform. It also describes how the copula model is used to model the joint distribution of underlying assets. By presenting significant results in discrete processes and showing how to transfer the results to their continuous counterparts, this text imparts an accessible, practical understanding of the subject. It helps readers not only grasp the theory of financial engineering, but also implement the theory in business.

Handbuch Modellbildung und Simulation in den Sozialwissenschaften

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Author: Norman Braun,Nicole J. Saam

Publisher: Springer-Verlag

ISBN: 3658011645

Category: Social Science

Page: 1079

View: 8292

Das Handbuch Modellbildung und Simulation in den Sozialwissenschaften bietet in 37 Artikeln einen umfassenden Überblick über sozialwissenschaftliche Modellbildung und Simulation. Es vermittelt wissenschaftstheoretische und methodische Grundlagen sowie den Stand der Forschung in den wichtigsten Anwendungsgebieten. Behandelt werden realistische, strukturalistische und konstruktivistische Zugriffe auf Modellbildung und Simulation, bedeutende Methoden und Typen der Modellierung (u.a. stochastische Prozesse und Bayes-Verfahren, nutzen- und spieltheoretische Modellierungen) und Ansätze der Computersimulation (z.B. Multi-Agenten-Modelle, zelluläre Automaten, neuronale Netze, Small Worlds). Die Anwendungskapitel befassen sich u.a. mit sozialen Dilemmata, sozialen Normen, Innovation und Diffusion, Herrschaft und Organisation, Gewalt und Krieg.

Introduction to Probability with R

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Author: Kenneth Baclawski

Publisher: CRC Press

ISBN: 9781420065220

Category: Mathematics

Page: 384

View: 9920

Based on a popular course taught by the late Gian-Carlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. Although the R programs are small in length, they are just as sophisticated and powerful as longer programs in other languages. This brevity makes it easy for students to become proficient in R. This calculus-based introduction organizes the material around key themes. One of the most important themes centers on viewing probability as a way to look at the world, helping students think and reason probabilistically. The text also shows how to combine and link stochastic processes to form more complex processes that are better models of natural phenomena. In addition, it presents a unified treatment of transforms, such as Laplace, Fourier, and z; the foundations of fundamental stochastic processes using entropy and information; and an introduction to Markov chains from various viewpoints. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. The book has an accompanying website with more information.