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Elementary Applications of Probability Theory, Tuckwell, Henry C.


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Цена: 63280.00T
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Автор: Tuckwell, Henry C.
Название:  Elementary Applications of Probability Theory
ISBN: 9780367449056
Издательство: Taylor&Francis
Классификация:
ISBN-10: 0367449056
Обложка/Формат: Paperback
Страницы: 308
Вес: 0.57 кг.
Дата издания: 29.11.2019
Серия: Chapman & hall/crc texts in statistical science
Язык: English
Издание: 2 ed
Размер: 234 x 156 x 17
Читательская аудитория: Technical / manuals
Основная тема: Mathematics & Statistics for Engineers
Подзаголовок: With an introduction to stochastic differential equations
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Европейский союз
Описание: This book provides a clear and straightforward introduction to applications of probability theory with examples given in the biological sciences, engineering, and physical, social and statistical sciences. It also introduces the topic of stochastic differential equations and their applications.

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
Рейтинг:
Цена: 74510.00 T
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.

Matrix Differential Calculus with Applications in Statistics and Econometrics

Автор: Jan R. Magnus, Heinz Neudecker
Название: Matrix Differential Calculus with Applications in Statistics and Econometrics
ISBN: 1119541204 ISBN-13(EAN): 9781119541202
Издательство: Wiley
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Цена: 93930.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

A brand new, fully updated edition of a popular classic on matrix differential calculus with applications in statistics and econometrics

This exhaustive, self-contained book on matrix theory and matrix differential calculus provides a treatment of matrix calculus based on differentials and shows how easy it is to use this theory once you have mastered the technique. Jan Magnus, who, along with the late Heinz Neudecker, pioneered the theory, develops it further in this new edition and provides many examples along the way to support it.

Matrix calculus has become an essential tool for quantitative methods in a large number of applications, ranging from social and behavioral sciences to econometrics. It is still relevant and used today in a wide range of subjects such as the biosciences and psychology. Matrix Differential Calculus with Applications in Statistics and Econometrics, Third Edition contains all of the essentials of multivariable calculus with an emphasis on the use of differentials. It starts by presenting a concise, yet thorough overview of matrix algebra, then goes on to develop the theory of differentials. The rest of the text combines the theory and application of matrix differential calculus, providing the practitioner and researcher with both a quick review and a detailed reference.

  • Fulfills the need for an updated and unified treatment of matrix differential calculus
  • Contains many new examples and exercises based on questions asked of the author over the years
  • Covers new developments in field and features new applications
  • Written by a leading expert and pioneer of the theory
  • Part of the Wiley Series in Probability and Statistics

Matrix Differential Calculus With Applications in Statistics and Econometrics Third Edition is an ideal text for graduate students and academics studying the subject, as well as for postgraduates and specialists working in biosciences and psychology.


Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

A Course in Probability Theory, Revised Edition,

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: 83080.00 T
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.

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: 70740.00 T
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.

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
Рейтинг:
Цена: 69870.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides an introduction to probability theory and its applications.

Probability Theory with Applications

Автор: Rao M.M., Swift R.J.
Название: Probability Theory with Applications
ISBN: 0387277307 ISBN-13(EAN): 9780387277301
Издательство: Springer
Рейтинг:
Цена: 102480.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is a revised and expanded edition of a successful graduate and reference text. The material in the book is designed for a standard graduate course on probability theory, including some important applications. This new edition contains a detailed treatment of the core area of probability, and both structural and limit results are presented in full detail. Compared to the first edition, the material and presentation are better highlighted with several (small and large) alterations made to each chapter. Key features of the book include:

Elementary Probability with Applications

Автор: Rabinowitz , Larry
Название: Elementary Probability with Applications
ISBN: 036739362X ISBN-13(EAN): 9780367393625
Издательство: Taylor&Francis
Рейтинг:
Цена: 67360.00 T
Наличие на складе: Нет в наличии.
Описание: Provides an introduction to probability and its applications in the real world.

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: 102080.00 T
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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.

An Introduction to Probability Theory and Its Applications, Volume 1, 3rd Edition

Автор: Feller, William
Название: An Introduction to Probability Theory and Its Applications, Volume 1, 3rd Edition
ISBN: 0471257087 ISBN-13(EAN): 9780471257080
Издательство: Wiley
Рейтинг:
Цена: 260780.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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. Beginning with the background and very nature of probability theory, the book then proceeds through sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, stochastic processes, and more. The book's comprehensive approach provides a complete view of theory along with enlightening examples along the way.


Manifold Learning Theory and Applications

Автор: Ma
Название: Manifold Learning Theory and Applications
ISBN: 1439871094 ISBN-13(EAN): 9781439871096
Издательство: Taylor&Francis
Рейтинг:
Цена: 148010.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Trained to extract actionable information from large volumes of high-dimensional data, engineers and scientists often have trouble isolating meaningful low-dimensional structures hidden in their high-dimensional observations. Manifold learning, a groundbreaking technique designed to tackle these issues of dimensionality reduction, finds widespread application in machine learning, neural networks, pattern recognition, image processing, and computer vision.

Filling a void in the literature, Manifold Learning Theory and Applications incorporates state-of-the-art techniques in manifold learning with a solid theoretical and practical treatment of the subject. Comprehensive in its coverage, this pioneering work explores this novel modality from algorithm creation to successful implementation--offering examples of applications in medical, biometrics, multimedia, and computer vision. Emphasizing implementation, it highlights the various permutations of manifold learning in industry including manifold optimization, large scale manifold learning, semidefinite programming for embedding, manifold models for signal acquisition, compression and processing, and multi scale manifold.

Beginning with an introduction to manifold learning theories and applications, the book includes discussions on the relevance to nonlinear dimensionality reduction, clustering, graph-based subspace learning, spectral learning and embedding, extensions, and multi-manifold modeling. It synergizes cross-domain knowledge for interdisciplinary instructions, offers a rich set of specialized topics contributed by expert professionals and researchers from a variety of fields. Finally, the book discusses specific algorithms and methodologies using case studies to apply manifold learning for real-world problems.


Introduction to Probability with Statistical Applications

Автор: Schay G.
Название: Introduction to Probability with Statistical Applications
ISBN: 3319306189 ISBN-13(EAN): 9783319306186
Издательство: Springer
Рейтинг:
Цена: 62410.00 T
Наличие на складе: Нет в наличии.
Описание: Now inits second edition, this textbook serves as an introduction toprobability and statistics for non-mathematics majors who do not need theexhaustive detail and mathematical depth provided in more comprehensivetreatments of the subject. The presentation covers the mathematical laws ofrandom phenomena, including discrete and continuous random variables,expectation and variance, and common probability distributions such as thebinomial, Poisson, and normal distributions. More classical examples such asMontmort's problem, the ballot problem, and Bertrand’s paradox are nowincluded, along with applications such as the Maxwell-Boltzmann andBose-Einstein distributions in physics.Keyfeatures in new edition:* 35 newexercises* Expanded sectionon the algebra of sets *Expanded chapters on probabilities to include more classical examples* Newsection on regression* Onlineinstructors' manual containing solutions to all exercises


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