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.
Описание: Provides an introduction to probability theory and its applications.
Автор: Kallenberg Olav Название: Foundations of Modern Probability ISBN: 0387953132 ISBN-13(EAN): 9780387953137 Издательство: Springer Рейтинг: Цена: 9404 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: About the first edition: To sum it up, one can perhaps see a distinction among advanced probability books into those which are original and path-breaking in content, such as Levy's and Doob's well-known examples, and those which aim primarily to assimilate known material, such as Loeve's and more recently Rogers and Williams'. Seen in this light, Kallenberg's present book would have to qualify as the assimilation of probability par excellence. It is a great edifice of material, clearly and ingeniously presented, without any non-mathematical distractions. Readers wishing to venture into it may do so with confidence that they are in very capable hands.- Mathematical ReviewsThis new edition contains four new chapters as well as numerous improvements throughout the text. There are new chapters on measure Theory-key results, ergodic properties of Markov processes and large deviations.
Автор: Koralov Название: Theory of Probability and Random Processes ISBN: 3540254846 ISBN-13(EAN): 9783540254843 Издательство: Springer Рейтинг: Цена: 6269 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Описание: Updated to conform to Mathematica® 7.0, this second edition shows how to easily create simulations from templates and solve problems using Mathematica. Along with new sections on order statistics, transformations of multivariate normal random variables, and Brownian motion, this edition offers an expanded section on Markov chains, more example data of the normal distribution, and more attention on conditional expectation. It also includes additional problems from Actuarial Exam P as well as new examples, exercises, and data sets. The accompanying CD-ROM contains updated Mathematica notebooks and a revised solutions manual is available for qualifying instructors.
Описание: Probability is a vital measure in numerous disciplines, from bioinformatics and econometrics to finance/insurance and computer science. Developed from a
successful course, "Fundamental Probability" provides an engaging and hands on introduction to this important topic. Whilst the theory is explored in detail, this book also emphasises
practical applications, with the presentation of a large variety of examples and exercises, along with generous use of computational tools.Based on international teaching experience
with students of statistics, mathematics, finance and econometrics, the book presents new, innovative material alongside the classic theory.
It goes beyond standard
presentations by carefully introducing and discussing more complex subject matter, including a richer use of combinatorics, runs and occupancy distributions, various multivariate
sampling schemes, fat tailed distributions, and several basic concepts used in finance. It emphasises computational matters and programming methods via generous use of examples in
MATLAB. It includes a large, self contained Calculus/Analysis appendix with derivations of all required tools, such as Leibniz' rule, exchange of derivative and integral, Fubini's
theorem, and univariate and multivariate Taylor series.
It presents over 150 end of chapter exercises, graded in terms of their difficulty, and accompanied by a full set of
solutions online.This book is intended as an introduction to the theory of probability for students in biology, mathematics, statistics, economics, engineering, finance, and computer
science who possess the prerequisite knowledge of basic calculus and linear algebra.
Описание: Scientists in optics are increasingly confronted with problems that are of a random nature and that require a working knowledge of probability and statistics for their solution. This textbook develops these subjects within the context of optics using a problem-solving approach. All methods are explicitly derived and can be traced back to three simple axioms given at the outset. Students with some previous exposure to Fourier optics or linear theory will find the material particularly absorbing and easy to understand.This third edition contains many new applications to optical and physical phenomena. This includes a method of estimating probability laws exactly, by regarding them as laws of physics to be determined using a new variational principle.
Описание: Details several topics, from standard ones such as order statistics, multivariate normal, and convergence concepts, to more advanced ones. This book places emphasis on the numeric computation of convolutions of random variables, via numeric integration, inversion theorems, fast Fourier transforms, saddlepoint approximations, and simulation.
Автор: Gamerman, Dani. Название: Markov Chain Monte Carlo ISBN: 1584885874 ISBN-13(EAN): 9781584885870 Издательство: Taylor&Francis Рейтинг: Цена: 9123 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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: Robert B. Ash Название: Probability & Measure Theory, ISBN: 0120652021 ISBN-13(EAN): 9780120652020 Издательство: Elsevier Science Рейтинг: Цена: 9818 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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