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An Introduction to Random Sets, Nguyen, Hung T.


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Автор: Nguyen, Hung T.
Название:  An Introduction to Random Sets
ISBN: 9780367390990
Издательство: Taylor&Francis
Классификация:




ISBN-10: 036739099X
Обложка/Формат: Paperback
Страницы: 268
Вес: 1.09 кг.
Дата издания: 27.09.2019
Язык: English
Иллюстрации: 6 tables, black and white; 1 illustrations, black and white
Размер: 231 x 152 x 18
Читательская аудитория: Professional & vocational
Основная тема: Set Theory
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

The study of random sets is a large and rapidly growing area with connections to many areas of mathematics and applications in widely varying disciplines, from economics and decision theory to biostatistics and image analysis. The drawback to such diversity is that the research reports are scattered throughout the literature, with the result that in science and engineering, and even in the statistics community, the topic is not well known and much of the enormous potential of random sets remains untapped.

An Introduction to Random Sets provides a friendly but solid initiation into the theory of random sets. It builds the foundation for studying random set data, which, viewed as imprecise or incomplete observations, are ubiquitous in todays technological society. The author, widely known for his best-selling A First Course in Fuzzy Logic text as well as his pioneering work in random sets, explores motivations, such as coarse data analysis and uncertainty analysis in intelligent systems, for studying random sets as stochastic models. Other topics include random closed sets, related uncertainty measures, the Choquet integral, the convergence of capacity functionals, and the statistical framework for set-valued observations. An abundance of examples and exercises reinforce the concepts discussed.

Designed as a textbook for a course at the advanced undergraduate or beginning graduate level, this book will serve equally well for self-study and as a reference for researchers in fields such as statistics, mathematics, engineering, and computer science.




Introduction to random matrices

Автор: Anderson, Greg W. Guionnet, Alice Zeitouni, Ofer
Название: Introduction to random matrices
ISBN: 0521194520 ISBN-13(EAN): 9780521194525
Издательство: Cambridge Academ
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Цена: 11088.00 р.
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Описание: The theory of random matrices plays an important role in many areas of pure mathematics. This rigorous introduction is specifically designed for graduate students in mathematics or related sciences, who have a background in probability theory but have not been exposed to advanced notions of functional analysis, algebra or geometry.

Introduction to Stochastic Integration

Автор: Kuo
Название: Introduction to Stochastic Integration
ISBN: 0387287205 ISBN-13(EAN): 9780387287201
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Also called Ito calculus, the theory of stochastic integration has applications in virtually every scientific area involving random functions. This introductory textbook provides a concise introduction to the Ito calculus. From the reviews:"Introduction to Stochastic Integration is exactly what the title says.

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: 10480.00 р.
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Описание: Provides an introduction to probability theory and its applications.

An Introduction to Markov Processes

Автор: Stroock Daniel W.
Название: An Introduction to Markov Processes
ISBN: 3540234519 ISBN-13(EAN): 9783540234517
Издательство: Springer
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Цена: 8384.00 р.
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Описание: This book provides a rigorous but elementary introduction to the theory of Markov Processes on a countable state space. It should be accessible to students with a solid undergraduate background in mathematics, including students from engineering, economics, physics, and biology. Topics covered are: Doeblin's theory, general ergodic properties, and continuous time processes. A whole chapter is devoted to reversible processes and the use of their associated Dirichlet forms to estimate the rate of convergence to equilibrium.

Introduction to High-Dimensional Statistics

Автор: Giraud
Название: Introduction to High-Dimensional Statistics
ISBN: 1482237946 ISBN-13(EAN): 9781482237948
Издательство: Taylor&Francis
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Цена: 9645.00 р.
Наличие на складе: Поставка под заказ.

Описание: Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise. Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for handling high-dimensional data. The book is intended to expose the reader to the key concepts and ideas in the most simple settings possible while avoiding unnecessary technicalities. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this highly accessible text: Describes the challenges related to the analysis of high-dimensional data Covers cutting-edge statistical methods including model selection, sparsity and the lasso, aggregation, and learning theory Provides detailed exercises at the end of every chapter with collaborative solutions on a wikisite Illustrates concepts with simple but clear practical examples Introduction to High-Dimensional Statistics is suitable for graduate students and researchers interested in discovering modern statistics for massive data. It can be used as a graduate text or for self-study.

Brownian Motion: An Introduction to Stochastic Processes

Автор: Rene L. Schilling, Lothar Partzsch
Название: Brownian Motion: An Introduction to Stochastic Processes
ISBN: 3110307294 ISBN-13(EAN): 9783110307290
Издательство: Walter de Gruyter
Цена: 6368.00 р.
Наличие на складе: Нет в наличии.

Описание: Brownian motion is one of the most important stochastic processes in continuous time and with continuous state space. Within the realm of stochastic processes, Brownian motion is at the intersection of Gaussian processes, martingales, Markov processes, diffusions and random fractals, and it has influenced the study of these topics. Its central position within mathematics is matched by numerous applications in science, engineering and mathematical finance. Often textbooks on probability theory cover, if at all, Brownian motion only briefly. On the other hand, there is a considerable gap to more specialized texts on Brownian motion which is not so easy to overcome for the novice. The authors’ aim was to write a book which can be used as an introduction to Brownian motion and stochastic calculus, and as a first course in continuous-time and continuous-state Markov processes. They also wanted to have a text which would be both a readily accessible mathematical back-up for contemporary applications (such as mathematical finance) and a foundation to get easy access to advanced monographs. This textbook, tailored to the needs of graduate and advanced undergraduate students, covers Brownian motion, starting from its elementary properties, certain distributional aspects, path properties, and leading to stochastic calculus based on Brownian motion. It also includes numerical recipes for the simulation of Brownian motion.

Introduction to Applied Linear Algebra

Автор: Boyd Stephen
Название: Introduction to Applied Linear Algebra
ISBN: 1316518965 ISBN-13(EAN): 9781316518960
Издательство: Cambridge Academ
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Цена: 6811.00 р.
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Описание: A groundbreaking introductory textbook covering the linear algebra methods needed for data science and engineering applications. It combines straightforward explanations with numerous practical examples and exercises from data science, machine learning and artificial intelligence, signal and image processing, navigation, control, and finance.

Introduction to Probability, Second Edition

Автор: Joseph K. Blitzstein, Jessica Hwang
Название: Introduction to Probability, Second Edition
ISBN: 1138369918 ISBN-13(EAN): 9781138369917
Издательство: Taylor&Francis
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Цена: 11176.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Assumes one-semester of calculus. "Stories" make distributions (Normal, Binomial, Poisson that are widely-used in statistics) easier to remember, understand. Many books write down formulas without explaining clearly why these particular distributions are important or how they are all connected.

Introduction to Mathematical Portfolio Theory

Автор: Joshi
Название: Introduction to Mathematical Portfolio Theory
ISBN: 1107042313 ISBN-13(EAN): 9781107042315
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: A concise yet comprehensive guide to the mathematics of portfolio theory from a modelling perspective, with discussion of the assumptions, limitations and implementations of the models as well as the theory underlying them. Aimed at advanced undergraduates, this book can be used for self-study or as a course text.

An Introduction to Quantitative Finance

Автор: Blyth Stephen
Название: An Introduction to Quantitative Finance
ISBN: 0199666598 ISBN-13(EAN): 9780199666591
Издательство: Oxford Academ
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Цена: 6810.00 р.
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Описание: The quantitative nature of complex financial transactions makes them a fascinating subject area for mathematicians of all types. This book gives an insight into financial engineering while building on introductory probability courses by detailing one of the most fascinating applications of the subject.

An Introduction to the Bootstrap

Автор: Efron
Название: An Introduction to the Bootstrap
ISBN: 0412042312 ISBN-13(EAN): 9780412042317
Издательство: Taylor&Francis
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Цена: 22968.00 р.
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Описание: An exploration of the many different bootstrap techniques. It discusses useful statistical techniques through real data examples and covers nonparametric regression, density estimation, classification trees, and least median squares regression. There are numerous exercises.

Introduction to Nonparametric Estimation

Автор: Alexandre B. Tsybakov
Название: Introduction to Nonparametric Estimation
ISBN: 0387790519 ISBN-13(EAN): 9780387790510
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Presents basic nonparametric regression and density estimators and analyzes their properties. This book covers minimax lower bounds, and develops advanced topics such as: Pinsker`s theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity.


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