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Computational Probability, Winfried K. Grassmann


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Автор: Winfried K. Grassmann
Название:  Computational Probability
ISBN: 9781441951007
Издательство: Springer
Классификация:

ISBN-10: 1441951008
Обложка/Формат: Paperback
Страницы: 490
Вес: 0.69 кг.
Дата издания: 06.12.2010
Серия: International Series in Operations Research & Management Science
Язык: English
Размер: 234 x 156 x 26
Основная тема: Business and Management
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Markov modeling has found applications in many areas, three of which are described in detail: Chapter 10 analyzes discrete-time queues, Chapter 11 describes networks of queues, and Chapter 12 deals with reliability theory.


Theory of Probability and Random Processes

Автор: Koralov
Название: Theory of Probability and Random Processes
ISBN: 3540254846 ISBN-13(EAN): 9783540254843
Издательство: Springer
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Цена: 8384.00 р.
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Описание: A one-year course in probability theory and the theory of random processes, taught at Princeton University to undergraduate and graduate students, forms the core of the content of this bookIt is structured in two parts: the first part providing a detailed discussion of Lebesgue integration, Markov chains, random walks, laws of large numbers, limit theorems, and their relation to Renormalization Group theory. The second part includes the theory of stationary random processes, martingales, generalized random processes, Brownian motion, stochastic integrals, and stochastic differential equations. One section is devoted to the theory of Gibbs random fields.This material is essential to many undergraduate and graduate courses. The book can also serve as a reference for scientists using modern probability theory in their research.

Elementary probability for applications

Автор: Durrett, Rick
Название: Elementary probability for applications
ISBN: 0521867568 ISBN-13(EAN): 9780521867566
Издательство: Cambridge Academ
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Цена: 10611.00 р.
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Описание: This is a perfect one-semester introduction to probability, for students who are familiar with basic calculus. The lively style reflects the author`s philosophy that the best way to learn probability is to see it in action, and he gives over 200 examples from genetics, sports, finance, and current events.

Computational Probability

Автор: John H. Drew; Diane L. Evans; Andrew G. Glen; Lawr
Название: Computational Probability
ISBN: 3319433210 ISBN-13(EAN): 9783319433219
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL). The book examines and presents, in a systematic manner, computational probability methods that encompass data structures and algorithms. The developed techniques address problems that require exact probability calculations, many of which have been considered intractable in the past. The book addresses the plight of the probabilist by providing algorithms to perform calculations associated with random variables.

Computational Probability: Algorithms and Applications in the Mathematical Sciences, 2nd Edition begins with an introductory chapter that contains short examples involving the elementary use of APPL. Chapter 2 reviews the Maple data structures and functions necessary to implement APPL. This is followed by a discussion of the development of the data structures and algorithms (Chapters 3–6 for continuous random variables and Chapters 7–9 for discrete random variables) used in APPL. The book concludes with Chapters 10–15 introducing a sampling of various applications in the mathematical sciences. This book should appeal to researchers in the mathematical sciences with an interest in applied probability and instructors using the book for a special topics course in computational probability taught in a mathematics, statistics, operations research, management science, or industrial engineering department.
Computational Probability Applications

Автор: Andrew G. Glen; Lawrence M. Leemis
Название: Computational Probability Applications
ISBN: 3319433156 ISBN-13(EAN): 9783319433158
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This focuses on the developing field of building probability models with the power of symbolic algebra systems. The book combines the uses of symbolic algebra with probabilistic/stochastic application and highlights the applications in a variety of contexts. The research explored in each chapter is unified by the use of A Probability Programming Language (APPL) to achieve the modeling objectives. APPL, as a research tool, enables a probabilist or statistician the ability to explore new ideas, methods, and models. Furthermore, as an open-source language, it sets the foundation for future algorithms to augment the original code.

Computational Probability Applications is comprised of fifteen chapters, each presenting a specific application of computational probability using the APPL modeling and computer language. The chapter topics include using inverse gamma as a survival distribution, linear approximations of probability density functions, and also moment-ratio diagrams for univariate distributions. These works highlight interesting examples, often done by undergraduate students and graduate students that can serve as templates for future work. In addition, this book should appeal to researchers and practitioners in a range of fields including probability, statistics, engineering, finance, neuroscience, and economics.
Intermediate Probability - A Computational Approach

Автор: Paolella
Название: Intermediate Probability - A Computational Approach
ISBN: 0470026375 ISBN-13(EAN): 9780470026373
Издательство: Wiley
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Цена: 20109.00 р.
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Описание: Many of the traditional and older advanced texts do not cover the newer topics in probability such as Paretian distribution and noncentral distributions and saddlepoint approximation. The material is only covered in research monographs or in journal articles.

Computational Statistics Handbook with MATLAB

Автор: Martinez Wendy L.
Название: Computational Statistics Handbook with MATLAB
ISBN: 1466592737 ISBN-13(EAN): 9781466592735
Издательство: Taylor&Francis
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Цена: 16078.00 р.
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Описание:

A Strong Practical Focus on Applications and Algorithms
Computational Statistics Handbook with MATLAB(R), Third Edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the implementation of the methods.

New to the Third Edition
This third edition is updated with the latest version of MATLAB and the corresponding version of the Statistics and Machine Learning Toolbox. It also incorporates new sections on the nearest neighbor classifier, support vector machines, model checking and regularization, partial least squares regression, and multivariate adaptive regression splines.

Web Resource
The authors include algorithmic descriptions of the procedures as well as examples that illustrate the use of algorithms in data analysis. The MATLAB code, examples, and data sets are available online.

Exercises in Probability

Автор: Chaumont
Название: Exercises in Probability
ISBN: 1107606551 ISBN-13(EAN): 9781107606555
Издательство: Cambridge Academ
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Цена: 8870.00 р.
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Описание: Ideal for independent study or as a companion to a course in advanced probability theory, this book now includes over 100 exercises. In each case, the authors provide a detailed solution and references for preliminary and further reading. Insightful notes help to set the exercises in context.

Markov Chain Monte Carlo

Автор: Gamerman, Dani.
Название: Markov Chain Monte Carlo
ISBN: 1584885874 ISBN-13(EAN): 9781584885870
Издательство: Taylor&Francis
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Цена: 15312.00 р.
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Описание: Incorporating changes in theory and highlighting various applications, this book presents a comprehensive introduction to the methods of Markov Chain Monte Carlo (MCMC) simulation technique. It incorporates the developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection.

Intuitive Probability and Random Processes using MATLAB®

Автор: Kay
Название: Intuitive Probability and Random Processes using MATLAB®
ISBN: 0387241574 ISBN-13(EAN): 9780387241579
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Offering an introduction to probability and random processes, this book merges theory with practice. It is suitable for undergraduate and first-year graduate students in engineering, practicing engineers as well as others having appropriate mathematical background.

Digital Dice: Computational Solutions to Practical Probability Problems (New in Paperback)

Автор: Nahin Paul J.
Название: Digital Dice: Computational Solutions to Practical Probability Problems (New in Paperback)
ISBN: 0691158215 ISBN-13(EAN): 9780691158211
Издательство: Wiley
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Цена: 2691.00 р.
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Описание: Some probability problems are so difficult that they stump the smartest mathematicians. But even the hardest of these problems can often be solved with a computer and a Monte Carlo simulation, in which a random-number generator simulates a physical process, such as a million rolls of a pair of dice. This is what Digital Dice is all about: how to ge

A Course in Computational Probability and Statistics

Автор: Walter Freiberger; Ulf Grenander
Название: A Course in Computational Probability and Statistics
ISBN: 0387900292 ISBN-13(EAN): 9780387900292
Издательство: Springer
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Цена: 12157.00 р.
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Описание: It had its origin in a project initiated jointly with the IBM Cambridge Scien- tific Center, particularly with Dr. Rhett Tsao, then of that Center. Professors Donald McClure and Richard Vitale of the Division of Applied Mathematics at Brown University contributed greatly to the project and taught courses in its spirit.

Computational Probability

Автор: Winfried K. Grassmann
Название: Computational Probability
ISBN: 0792386175 ISBN-13(EAN): 9780792386179
Издательство: Springer
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Цена: 41787.00 р.
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Описание: The objective of this text is to make topics such as queueing systems, stochastic Petri-nets and systems dealing with reliability more accessible. Topics covered include challenges in computational probability and obtaining the transition matrices for Markov chains.


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