An Introduction to Continuous-Time Stochastic Processes, Capasso
Автор: Capasso, Vincenzo Bakstein, David Название: Introduction to continuous-time stochastic processes ISBN: 1493927566 ISBN-13(EAN): 9781493927562 Издательство: Springer Цена: 9404 р. Наличие на складе: Невозможна поставка. Описание: An Introduction to Continuous-Time Stochastic Processes
Автор: Gallager Название: Stochastic Processes ISBN: 1107039754 ISBN-13(EAN): 9781107039759 Издательство: Cambridge Academ Рейтинг: Цена: 6901 р. Наличие на складе: Есть (1 шт.) Описание: This definitive textbook provides a solid introduction to discrete and continuous stochastic processes, tackling a complex field in a way that instils a deep understanding of the relevant mathematical principles, and develops an intuitive grasp of the way these principles can be applied to modelling real-world systems. It includes a careful review of elementary probability and detailed coverage of Poisson, Gaussian and Markov processes with richly varied queuing applications. The theory and applications of inference, hypothesis testing, estimation, random walks, large deviations, martingales and investments are developed. Written by one of the world's leading information theorists, evolving over twenty years of graduate classroom teaching and enriched by over 300 exercises, this is an exceptional resource for anyone looking to develop their understanding of stochastic processes.
Описание: Provides an introduction to probability theory and its applications.
Автор: Kuo Название: Introduction to Stochastic Integration ISBN: 0387287205 ISBN-13(EAN): 9780387287201 Издательство: Springer Рейтинг: Цена: 5224 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The theory of stochastic integration, also called the Ito calculus, has a large spectrum of applications in virtually every scientific area involving random functions, but it can be a very difficult subject for people without much mathematical background. The Ito calculus was originally motivated by the construction of Markov diffusion processes from infinitesimal generators. Previously, the construction of such processes required several steps, whereas Ito constructed these diffusion processes directly in a single step as the solutions of stochastic integral equations associated with the infinitesimal generators. Moreover, the properties of these diffusion processes can be derived from the stochastic integral equations and the Ito formula. This introductory textbook on stochastic integration provides a concise introduction to the Ito calculus, and covers the following topics:* Constructions of Brownian motion;* Stochastic integrals for Brownian motion and martingales;* The Ito formula;* Multiple Wiener-Ito integrals;* Stochastic differential equations;* Applications to finance, filtering theory, and electric circuits.The reader should have a background in advanced calculus and elementary probability theory, as well as a basic knowledge of measure theory and Hilbert spaces. Each chapter ends with a variety of exercises designed to help the reader further understand the material.Hui-Hsiung Kuo is the Nicholson Professor of Mathematics at Louisiana State University. He has delivered lectures on stochastic integration at Louisiana State University, Cheng Kung University, Meijo University, and University of Rome "Tor Vergata," among others. He is also the author of Gaussian Measures in Banach Spaces (Springer 1975), and White Noise Distribution Theory (CRC Press 1996), and a memoir of his childhood growing up in Taiwan, An Arrow Shot into the Sun (Abridge Books 2004).
Описание: Stochastic optimization problems arise in decision-making problems under uncertainty, and find various applications in economics and finance. On the other
hand, problems in finance have recently led to new developments in the theory of stochastic control. This volume provides a systematic treatment of stochastic optimization problems
applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations, and martingale duality
The theory is discussed in the context of recent developments in this field, with complete and detailed proofs, and is illustrated by means of concrete examples from
the world of finance: portfolio allocation, option hedging, real options, optimal investment, etc. This book is directed towards graduate students and researchers in mathematical finance,
and will also benefit applied mathematicians interested in financial applications and practitioners wishing to know more about the use of stochastic optimization methods in finance.
Описание: Many observed phenomena, from the changing health of a patient to values on the stock market, are characterised by quantities that vary over time:
stochastic processes are designed to study them. Much theoretical work has been done but virtually no modern books are available to show how the results can be applied. This book
fills that gap by introducing practical methods of applying stochastic processes to an audience knowledgeable only in basic statistics.
It covers almost all aspects of the
subject and presents the theory in an easily accessible form that is highlighted by application to many examples. These examples arise from dozens of areas, from sociology through
medicine to engineering. Complementing these are exercise sets making the book suited for introductory courses in stochastic processes.
Software (available from
www.cambridge.org) is provided for the freely available R system for the reader to apply to all the models presented.
Описание: Providing a novel approach to sparsity, this comprehensive book presents the theory of stochastic processes that are ruled by linear stochastic differential equations, and that admit a parsimonious representation in a matched wavelet-like basis. Two key themes are the statistical property of infinite divisibility, which leads to two distinct types of behaviour - Gaussian and sparse - and the structural link between linear stochastic processes and spline functions, which is exploited to simplify the mathematical analysis. The core of the book is devoted to investigating sparse processes, including a complete description of their transform-domain statistics. The final part develops practical signal-processing algorithms that are based on these models, with special emphasis on biomedical image reconstruction. This is an ideal reference for graduate students and researchers with an interest in signal/image processing, compressed sensing, approximation theory, machine learning, or statistics.
Описание: This comprehensive textbook provides an introduction to statistical methods for graduate engineers offering thorough coverage of important probability-related topics to aid in product and system design, reliability engineering, quality control, and more.
Автор: Dobrow Robert P. Название: Introduction to Stochastic Processes with R ISBN: 1118740653 ISBN-13(EAN): 9781118740651 Издательство: Wiley Рейтинг: Цена: 11377 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An introduction to stochastic processes through the use of R Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability
Описание: This user--friendly resource helps readers grasp the concepts of probability and stochastic processes, so they can apply them in professional engineering practice. The book presents concepts clearly as a sequence of building blocks that are identified either as an axiom, definition, or theorem. This approach provides a better understanding of the material, which can be used to solve practical problems.
Автор: Parzen, Emanuel Название: Stochastic processes ISBN: 0898714419 ISBN-13(EAN): 9780898714418 Издательство: Eurospan Рейтинг: Цена: 7874 р. Наличие на складе: Поставка под заказ.
Описание: This introductory textbook explains how and why probability models are applied to scientific fields such as medicine, biology, physics, oceanography, economics, and psychology to solve problems about stochastic processes. It does not just show how a problem is solved but explains why by formulating questions and first steps in the solutions.
Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
Описание: Delineates stochastic processes, emphasizing applications in biology. This book is organized according to the three types of stochastic processes: discrete time Markov chains, continuous time Markov chains and continuous time and state Markov processes. It contains a chapter on the biological applications of stochastic differential equations.
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