Probability Theory on Vector Spaces III, D Szynal; A. Weron
Автор: Koralov Название: Theory of Probability and Random Processes ISBN: 3540254846 ISBN-13(EAN): 9783540254843 Издательство: Springer Рейтинг: Цена: 8384.00 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.
Автор: Durrett, Rick Название: Elementary probability for applications ISBN: 0521867568 ISBN-13(EAN): 9780521867566 Издательство: Cambridge Academ Рейтинг: Цена: 10611.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Описание: Provides an introduction to probability theory and its applications.
Автор: A. Weron Название: Probability Theory on Vector Spaces II ISBN: 3540102531 ISBN-13(EAN): 9783540102533 Издательство: Springer Рейтинг: Цена: 4884.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Gamerman, Dani. Название: Markov Chain Monte Carlo ISBN: 1584885874 ISBN-13(EAN): 9781584885870 Издательство: Taylor&Francis Рейтинг: Цена: 15312.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: A. Beck Название: Probability in Banach Spaces III ISBN: 354010822X ISBN-13(EAN): 9783540108221 Издательство: Springer Рейтинг: Цена: 4884.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: S.V. Anulova; Yurij V. Prokhorov; P.B. Slater; Alb Название: Probability Theory III ISBN: 3642081223 ISBN-13(EAN): 9783642081224 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume of the Encyclopaedia is a survey of stochastic calculus, an increasingly important part of probability, authored by well-known experts in the field. The book addresses graduate students and researchers in probability theory and mathematical statistics, as well as physicists and engineers who need to apply stochastic methods.
Автор: Kai Lai Chung Название: A Course in Probability Theory, Revised Edition, ISBN: 0121741516 ISBN-13(EAN): 9780121741518 Издательство: Elsevier Science Рейтинг: Цена: 12462.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Название: Probability Theory and Statistical Inference ISBN: 0521424089 ISBN-13(EAN): 9780521424080 Издательство: Cambridge Academ Рейтинг: Цена: 7285.00 р. Наличие на складе: Поставка под заказ.
Описание: This major new textbook from a distinguished econometrician is intended for students taking introductory courses in probability theory and statistical inference. No prior knowledge other than a basic familiarity with descriptive statistics is assumed. The primary objective of this book is to establish the framework for the empirical modelling of observational (non-experimental) data. This framework known as 'Probabilistic Reduction' is formulated with a view to accommodating the peculiarities of observational (as opposed to experimental) data in a unifying and logically coherent way. Probability Theory and Statistical Inference differs from traditional textbooks in so far as it emphasizes concepts, ideas, notions and procedures which are appropriate for modelling observational data. Aimed at students at second-year undergraduate level and above studying econometrics and economics, this textbook will also be useful for students in other disciplines which make extensive use of observational data, including finance, biology, sociology and psychology and climatology.
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