Описание: Presents elementary probability theory with applications that illustrate the theory. This book reviews the basic elements of differential calculus which are used in the material to follow. It is suitable for students in pure and applied sciences such as mathematics, engineering, computer science, finance and economics.
Описание: A complete guide to the theory and practical applications of probability theory An Introduction to Probability Theory and Its Applications uniquely blends a comprehensive overview of probability theory with the real-world application of that theory.
Автор: M. M. Rao Название: Probability Theory with Applications, ISBN: 0125804806 ISBN-13(EAN): 9780125804806 Издательство: Elsevier Science Рейтинг: Цена: 5429 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Serves as a comprehensive treatment of the fundamentals of probability and statistical inference. This textbook helps readers to advance to topics such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. It discusses modes of convergence of sequences of random variables.
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.
Автор: Ok, E. Название: Real analysis with economic applications ISBN: 0691117683 ISBN-13(EAN): 9780691117683 Издательство: Wiley Рейтинг: Цена: 12474 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Addressing the topics of real analysis, this book discusses the elements of order theory, convex analysis, optimization, correspondences, linear and nonlinear functional analysis, fixed-point theory, dynamic programming, and calculus of variations. It includes fixed point theorems and applications to functional equations and optimization theory.
Автор: Edited by Timothy J. Ross Название: Fuzzy Logic and Probability Applications ISBN: 0898715253 ISBN-13(EAN): 9780898715255 Издательство: Eurospan Рейтинг: Цена: 17179 р. Наличие на складе: Невозможна поставка.
Описание: Probabilists and fuzzy enthusiasts tend to disagree about which philosophy is best and they rarely work together. As a result, textbooks usually suggest only one of these methods for problem solving, but not both. This book is an exception. The authors, investigators from both fields, have combined their talents to provide a practical guide showing that both fuzzy logic and probability have their place in the world of problem solving. They work together with mutual benefit for both disciplines, providing scientists and engineers with examples of and insight into the best tool for solving problems involving uncertainty. Fuzzy Logic and Probability Applications: Bridging the Gap makes an honest effort to show both the shortcomings and benefits of each technique, and even demonstrates useful combinations of the two. It provides clear descriptions of both fuzzy logic and probability, as well as the theoretical background, examples.
Описание: Contributed by world renowned researchers, the book features a wide range of important topics in modern statistical theory and methodology, economics and
finance, ecology, education, health and sports studies, and computer and IT-data mining. It is accessible to students and of interest to experts. Many of the contributions are concerned
with theoretical innovations, but all have applications in view, and some contain illustrations of the applied methods or photos of historic mathematicians.
A few of the notable
contributors are Ejaz Ahmed (Windsor), Joe Gani (ANU), Roger Gay (Monash), Atsuhiro Hayashi (NCUEE, Tokyo), Markus Hegland (ANU), Chris Heyde (ANU/Columbia), Jeff Hun
er (Massey), Phil Lewis (Canberra), Heinz Neudecker (Amsterdam), Graham Pollard (Canberra), Simo Puntanen (Tampere), George Styan (McGill), and Goetz Trenkler (Dortmund).
Описание: Probability and Statistics are as much about intuition and problem solving as they are about theorem proving. Because of this, students can find it very difficult to make a successful transition from lectures to examinations to practice, since the problems involved can vary so much in nature. Since the subject is critical in many modern applications such as mathematical finance, quantitative management, telecommunications, signal processing, bioinformatics, as well as traditional ones such as insurance, social science andengineering, the authors have rectified deficiencies in traditional lecture-based methods by collecting together a wealth of exercises with complete solutions, adapted to needs and skills of students. Following on from the success of Probability and Statistics by Example: Basic Probability and Statistics, the authors here concentrate on random processes, particularly Markov processes, emphasising modelsrather than general constructions. Basic mathematical facts are supplied as and when they are needed andhistorical information is sprinkled throughout.
Автор: Schinazi Название: Probability with Statistical Applications ISBN: 081768249X ISBN-13(EAN): 9780817682491 Издательство: Springer Цена: 6791 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This second edition of Probability With Statistical Applications offers a practical introduction to probability for undergraduates at all levels with different backgrounds and views towards applications. Calculus is a prerequisite for understanding the basic concepts, however the book is written with a sensitivity to students’ common difficulties with calculus that does not obscure the thorough treatment of the probability content. The first six chapters of this text neatly and concisely cover the material traditionally required by most undergraduate programs for a first course in probability.The comprehensive text includes a multitude of new examples and exercises, and careful revisions throughout. Particular attention is given to the expansion of the last three chapters of the book with the addition of two entirely new chapters on “Finding and Comparing Estimators” and “Multiple Linear Regression.” The classroom-tested material presented in this second edition textbook forms the basis for a second course introducing mathematical statistics.
Based on the author's course at NYU, Linear Algebra and Probability for Computer Science Applicationsgives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the chapters discuss relevant MATLAB(R) functions and features and give sample assignments in MATLAB; the author's website provides the MATLAB code from the book.
After an introductory chapter on MATLAB, the text is divided into two sections. The section on linear algebra gives an introduction to the theory of vectors, matrices, and linear transformations over the reals. It includes an extensive discussion on Gaussian elimination, geometric applications, and change of basis. It also introduces the issues of numerical stability and round-off error, the discrete Fourier transform, and singular value decomposition. The section on probability presents an introduction to the basic theory of probability and numerical random variables; later chapters discuss Markov models, Monte Carlo methods, information theory, and basic statistical techniques. The focus throughout is on topics and examples that are particularly relevant to computer science applications; for example, there is an extensive discussion on the use of hidden Markov models for tagging text and a discussion of the Zipf (inverse power law) distribution.
Examples and Programming Assignments The examples and programming assignments focus on computer science applications. The applications covered are drawn from a range of computer science areas, including computer graphics, computer vision, robotics, natural language processing, web search, machine learning, statistical analysis, game playing, graph theory, scientific computing, decision theory, coding, cryptography, network analysis, data compression, and signal processing.
Homework Problems Comprehensive problem sections include traditional calculation exercises, thought problems such as proofs, and programming assignments that involve creating MATLAB functions.
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