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A Modern Approach to Probability Theory, Fristedt Bert E., Gray Lawrence F.


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Цена: 7008р.
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Склад Англия: 368 шт.  Склад Америка: 104 шт.  
При оформлении заказа до: 25 окт 2019
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Автор: Fristedt Bert E., Gray Lawrence F.
Название:  A Modern Approach to Probability Theory
Издательство: Springer
Классификация:
Вероятность и статистика

ISBN: 0817638075
ISBN-13(EAN): 9780817638078
ISBN: 0-8176-3807-5
ISBN-13(EAN): 978-0-8176-3807-8
Обложка/Формат: Hardback
Страницы: 780
Вес: 1.26 кг.
Дата издания: 1996
Серия: Probability and its Applications
Язык: ENG
Иллюстрации: 1, black & white illustrations
Размер: 24.13 x 16.28 x 4.01 cm
Читательская аудитория: Postgraduate, research & scholarly
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Students and teachers of mathematics and related fields will find this book a comprehensive and modern approach to probability theory, providing the background and techniques to go from the beginning graduate level to the point of specialization in research areas of current interest. The book is designed for a two- or three-semester course, assuming only courses in undergraduate real analysis or rigorous advanced calculus, and some elementary linear algebra. A variety of applications—Bayesian statistics, financial mathematics, information theory, tomography, and signal processing—appear as threads to both enhance the understanding of the relevant mathematics and motivate students whose main interests are outside of pure areas.
Дополнительное описание: Круг читателей: Graduate students and researchers in probability, mathematics, theoretical statistics, computer science and engineering, and mathematical finance and economics.
Язык: eng





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: 5723 р.
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Описание: This clear and lively introduction to probability theory concentrates on the results that are the most useful for applications, including combinatorial probability and Markov chains. Concise and focused, it is designed for a one-semester introductory course in probability for students who have some familiarity with basic calculus. Reflecting the author's philosophy that the best way to learn probability is to see it in action, there are more than 350 problems and 200 examples. The examples contain all the old standards such as the birthday problem and Monty Hall, but also include a number of applications not found in other books, from areas as broad ranging as genetics, sports, finance, and inventory management.

Elementary Probability Theory / With Stochastic Processes and an Introduction to Mathematical Finance

Автор: Chung K. L., AitSahlia Farid
Название: Elementary Probability Theory / With Stochastic Processes and an Introduction to Mathematical Finance
ISBN: 038795578X ISBN-13(EAN): 9780387955780
Издательство: Springer
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Цена: 6544 р.
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Описание: Provides an introduction to probability theory and its applications.

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: 7523 р.
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Описание: Incorporating changes in theory and highlighting new applications, this book presents a concise, accessible, and comprehensive introduction to the methods of this valuable simulation technique. This second edition includes many new examples in the chapters on Gibbs sampling and Metropolis-Hastings algorithms. It incorporates all the recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection. It also features many worked examples and discusses computation using both R and WinBUGS. With additional exercises and selected solutions within the text, it offers all data sets and software for download from the Web.

A Modern Introduction to Probability and Statistics

Автор: Dekking
Название: A Modern Introduction to Probability and Statistics
ISBN: 1852338962 ISBN-13(EAN): 9781852338961
Издательство: Springer
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Цена: 3268 р.
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Описание: Using examples, often from real-life and using real data, this work shows how the fundamentals of probabilistic and statistical theories arise intuitively. It features over 350 exercises, half of which have answers, of which half have full solutions. It also covers standard statistics and probability material.

Автор: Kai Lai Chung
Название: A Course in Probability Theory, Revised Edition,
ISBN: 0121741516 ISBN-13(EAN): 9780121741518
Издательство: Elsevier Science
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Цена: 6634 р.
Наличие на складе: Ожидается поступление.

Описание: This book is designed for undergraduate programs and students and can also be used as a first-year graduate text in probability. It offers a broad perspective, building on the synopsis of measure and integration offered in Chapter two.

Probability & Measure Theory,

Автор: Robert B. Ash
Название: Probability & Measure Theory,
ISBN: 0120652021 ISBN-13(EAN): 9780120652020
Издательство: Elsevier Science
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Цена: 8784 р.
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Описание: Provides coverage of conditional probability and expectation, strong laws of large numbers, martingale theory, the central limit theorem, ergodic theory, and Brownian motion. This text for a graduate-level course in probability includes background topics in analysis.

Probability Theory / Independence, Interchangeability, Martingales

Автор: Chow Yuan Shih, Teicher Henry
Название: Probability Theory / Independence, Interchangeability, Martingales
ISBN: 0387406077 ISBN-13(EAN): 9780387406077
Издательство: Springer
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Цена: 5609 р.
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Описание: Now available in paperback. This is a text comprising the major theorems of probability theory and the measure theoretical foundations of the subject. The main topics treated are independence, interchangeability,and martingales; particular emphasis is placed upon stopping times, both as tools in proving theorems and as objects of interest themselves. No prior knowledge of measure theory is assumed and a unique feature of the book is the combined presentation of measure and probability. It is easily adapted for graduate students familar with measure theory as indicated by the guidelines in the preface. Special features include: A comprehensive treatment of the law of the iterated logarithm; the Marcinklewicz-Zygmund inequality, its extension to martingales and applications thereof;  development and applications of the second moment analogue of Wald's equation; limit theorems for martingale arrays, the central limit theorem for the interchangeable and martingale cases, moment convergence in the central limit theorem; complete discussion, including central limit theorem, of the random casting of r balls into n cells; recent martingale inequalities; Cram r-L vy theore and factor-closed families of distributions. This edition includes a section dealing with U-statistic, adds additional theorems and examples, and includes simpler versions of some proofs.

Mathematical Theory of Nonequilibrium Steady States / On the Frontier of Probability and Dynamical Systems

Автор: Jiang Da-Quan, Qian Min, Qian Ming-Ping
Название: Mathematical Theory of Nonequilibrium Steady States / On the Frontier of Probability and Dynamical Systems
ISBN: 3540206116 ISBN-13(EAN): 9783540206118
Издательство: Springer
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Цена: 4203 р.
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Описание: This volume provides a systematic mathematical exposition of the conceptual problems of nonequilibrium statistical physics, such as entropy production, irreversibility, and ordered phenomena. Markov chains, diffusion processes, and hyperbolic dynamical systems are used as mathematical models of physical systems. A measure-theoretic definition of entropy production rate and its formulae in various cases are given. It vanishes if and only if the stationary system is reversible and in equilibrium. Moreover, in the cases of Markov chains and diffusion processes on manifolds, it can be expressed in terms of circulations on directed cycles. Regarding entropy production fluctuations, the Gallavotti-Cohen fluctuation theorem is rigorously proved.

Lectures on Probability Theory and Statistics / Ecole d`EtГ© de ProbabilitГ©s de Saint-Flour XXXI - 2001

Автор: TavarГ© Simon, Zeitouni Ofer, Picard Jean
Название: Lectures on Probability Theory and Statistics / Ecole d`EtГ© de ProbabilitГ©s de Saint-Flour XXXI - 2001
ISBN: 3540208321 ISBN-13(EAN): 9783540208327
Издательство: Springer
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Цена: 5325 р.
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Описание: This volume contains lectures given at the 31st Probability Summer School in Saint-Flour (July 8-25, 2001). Simon Tavaré’s lectures serve as an introduction to the coalescent, and to inference for ancestral processes in population genetics. The stochastic computation methods described include rejection methods, importance sampling, Markov chain Monte Carlo, and approximate Bayesian methods. Ofer Zeitouni’s course on "Random Walks in Random Environment" presents systematically the tools that have been introduced to study the model. A fairly complete description of available results in dimension 1 is given. For higher dimension, the basic techniques and a discussion of some of the available results are provided. The contribution also includes an updated annotated bibliography and suggestions for further reading. Olivier Catoni's course appears separately.

Measure Theory and Probability Theory

Автор: Athreya
Название: Measure Theory and Probability Theory
ISBN: 038732903X ISBN-13(EAN): 9780387329031
Издательство: Springer
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Цена: 9349 р.
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Описание: This is a graduate level textbook on measure theory and probability theory. The book can be used as a text for a two semester sequence of courses in measure theory and probability theory, with an option to include supplemental material on stochastic processes and special topics. It is intended primarily for first year Ph.D. students in mathematics and statistics although mathematically advanced students from engineering and economics would also find the book useful. Prerequisites are kept to the minimal level of an understanding of basic real analysis concepts such as limits, continuity, differentiability, Riemann integration, and convergence of sequences and series. A review of this material is included in the appendix.The book starts with an informal introduction that provides some heuristics into the abstract concepts of measure and integration theory, which are then rigorously developed. The first part of the book can be used for a standard real analysis course for both mathematics and statistics Ph.D. students as it provides full coverage of topics such as the construction of Lebesgue-Stieltjes measures on real line and Euclidean spaces, the basic convergence theorems, L^p spaces, signed measures, Radon-Nikodym theorem, Lebesgue's decomposition theorem and the fundamental theorem of Lebesgue integration on R, product spaces and product measures, and Fubini-Tonelli theorems. It also provides an elementary introduction to Banach and Hilbert spaces, convolutions, Fourier series and Fourier and Plancherel transforms. Thus part I would be particularly useful for students in a typical Statistics Ph.D. program if a separate course on real analysis is not a standard requirement.Part II (chapters 6-13) provides full coverage of standard graduate level probability theory. It starts with Kolmogorov's probability model and Kolmogorov's existence theorem. It then treats thoroughly the laws of large numbers including renewal theory and ergodic theorems with applications and then weak convergence of probability distributions, characteristic functions, the Levy-Cramer continuity theorem and the central limit theorem as well as stable laws. It ends with conditional expectations and conditional probability, and an introduction to the theory of discrete time martingales.Part III (chapters 14-18) provides a modest coverage of discrete time Markov chains with countable and general state spaces, MCMC, continuous time discrete space jump Markov processes, Brownian motion, mixing sequences, bootstrap methods, and branching processes. It could be used for a topics/seminar course or as an introduction to stochastic processes.From the reviews: "...There are interesting and non-standard topics that are not usually included in a first course in measture-theoretic probability including Markov Chains and MCMC, the bootstrap, limit theorems for martingales and mixing sequences, Brownian motion and Markov processes. The material is well-suported with many end-of-chapter problems." D.L. McLeish for Short Book Reviews of the ISI, December 2006

Lectures on Probability Theory and Statistics / Ecole d`EtГ© de ProbabilitГ©s de Saint-Flour XXXII - 2002

Автор: Tsirelson Boris, Werner Wendelin, Picard Jean
Название: Lectures on Probability Theory and Statistics / Ecole d`EtГ© de ProbabilitГ©s de Saint-Flour XXXII - 2002
ISBN: 3540213163 ISBN-13(EAN): 9783540213161
Издательство: Springer
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Цена: 4203 р.
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Описание: This is yet another indispensable volume for all probabilists and collectors of the Saint-Flour series, and is also of great interest for mathematical physicists. It contains two of the three lecture courses given at the 32nd Probability Summer School in Saint-Flour (July 7-24, 2002). Tsirelson's lectures introduce the notion of nonclassical noise produced by very nonlinear functions of many independent random variables, for instance singular stochastic flows or oriented percolation. Werner's contribution gives a survey of results on conformal invariance, scaling limits and properties of some two-dimensional random curves. It provides a definition and properties of the Schramm-Loewner evolutions, computations (probabilities, critical exponents), the relation with critical exponents of planar Brownian motions, planar self-avoiding walks, critical percolation, loop-erased random walks and uniform spanning trees.

Paradoxes in Probability Theory and Mathematical Statistics

Автор: SzГ©kely GГЎbor J.
Название: Paradoxes in Probability Theory and Mathematical Statistics
ISBN: 1402002998 ISBN-13(EAN): 9781402002991
Издательство: Springer
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Цена: 5138 р.
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Описание: Paradoxes in Probability Theory and Mathematical Statistics


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