Stochastic Processes, Statistical Methods, and Engineering Mathematics, Malyarenko
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Bradley Efron , Trevor Hastie Название: Computer Age Statistical Inference, Student Edition ISBN: 1108823416 ISBN-13(EAN): 9781108823418 Издательство: Cambridge Academ Рейтинг: Цена: 5069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computing power has revolutionized the theory and practice of statistical inference. Now in paperback, and fortified with 130 class-tested exercises, this book explains modern statistical thinking from classical theories to state-of-the-art prediction algorithms. Anyone who applies statistical methods to data will value this landmark text.
Автор: Gallager Название: Stochastic Processes ISBN: 1107039754 ISBN-13(EAN): 9781107039759 Издательство: Cambridge Academ Рейтинг: Цена: 11246.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world`s leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.
Автор: Ghahramani Название: Fndmntls Of Probability 4E ISBN: 1498755097 ISBN-13(EAN): 9781498755092 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Поставка под заказ.
Описание: Covers topics used in a calculus-based junior-senior probability course. It can also be used as a text for a second course in probability. The historical roots and applications of many of the theorems and definitions are presented in detail, accompanied by suitable examples or counterexamples.
Описание: This book enables readers to understand, model, and predict complex dynamical systems using new methods with stochastic tools. The author presents a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. An emphasis is placed on the balance between computational efficiency and modeling accuracy, providing readers with ideas to build useful models in practice. Successful modeling of complex systems requires a comprehensive use of qualitative and quantitative modeling approaches, novel efficient computational methods, physical intuitions and thinking, as well as rigorous mathematical theories. As such, mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools are presented. Both theoretical and numerical approaches are included, allowing readers to choose suitable methods in different practical situations. The author provides practical examples and motivations when introducing various mathematical and stochastic tools and merges mathematics, statistics, information theory, computational science, and data science. In addition, the author discusses how to choose and apply suitable mathematical tools to several disciplines including pure and applied mathematics, physics, engineering, neural science, material science, climate and atmosphere, ocean science, and many others. Readers will not only learn detailed techniques for stochastic modeling and prediction, but will develop their intuition as well. Important topics in modeling and prediction including extreme events, high-dimensional systems, and multiscale features are discussed.
Автор: Martin Simon Название: Anomaly Detection in Random Heterogeneous Media ISBN: 3658109920 ISBN-13(EAN): 9783658109929 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph is concerned with the analysis and numerical solution of a stochastic inverse anomaly detection problem in electrical impedance tomography (EIT). Moreover, the author proposes an efficient numerical method in the framework of Bayesian inversion for the practical solution of the stochastic inverse anomaly detection problem.
Автор: Mandrekar Название: Stochastic Analysis For Gaussian Ra ISBN: 1498707815 ISBN-13(EAN): 9781498707817 Издательство: Taylor&Francis Рейтинг: Цена: 15312.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs).
The book begins with preliminary results on covariance and associated RKHS before introducing the Gaussian process and Gaussian random fields. The authors use chaos expansion to define the Skorokhod integral, which generalizes the It integral. They show how the Skorokhod integral is a dual operator of Skorokhod differentiation and the divergence operator of Malliavin. The authors also present Gaussian processes indexed by real numbers and obtain a Kallianpur-Striebel Bayes' formula for the filtering problem. After discussing the problem of equivalence and singularity of Gaussian random fields (including a generalization of the Girsanov theorem), the book concludes with the Markov property of Gaussian random fields indexed by measures and generalized Gaussian random fields indexed by Schwartz space. The Markov property for generalized random fields is connected to the Markov process generated by a Dirichlet form.
Автор: Reinhard Hopfner Название: Asymptotic Statistics: With a View to Stochastic Processes ISBN: 3110250241 ISBN-13(EAN): 9783110250244 Издательство: Walter de Gruyter Цена: 7429.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook is devoted to the general asymptotic theory of statistical experiments. Local asymptotics for statistical models in the sense of local asymptotic (mixed) normality or local asymptotic quadraticity make up the core of the book. Numerous examples deal with classical independent and identically distributed models and with stochastic processes. The book can be read in different ways, according to possibly different mathematical preferences of the reader. One reader may focus on the statistical theory, and thus on the chapters about Gaussian shift models, mixed normal and quadratic models, and on local asymptotics where the limit model is a Gaussian shift or a mixed normal or a quadratic experiment (LAN, LAMN, LAQ). Another reader may prefer an introduction to stochastic process models where given statistical results apply, and thus concentrate on subsections or chapters on likelihood ratio processes and some diffusion type models where LAN, LAMN or LAQ occurs. Finally, readers might put together both aspects. The book is suitable for graduate students starting to work in statistics of stochastic processes, as well as for researchers interested in a precise introduction to this area.
Описание: Part I: Stochastic Chemical Reactions.- Test Models for Statistical Inference: Two-Dimensional Reaction Systems Displaying Limit Cycle Bifurcations and Bistability.- Importance Sampling for Metastable and Multiscale Dynamical Systems.- Multiscale Simulation of Stochastic Reaction-diffusion Networks.- Part II: Stochastic Numerical Approaches, Algorithms and Coarse-Grained Simulations.- Numerical Methods for Ergodic SDEs: When Stochastic Integration Meets Geometric Integration.-Stability and Strong Convergence for Spatial Stochastic Kinetics.- The T cells in an Ageing Virtual Mouse.- Part III: Analysis of Stochastic Dynamical Systems for Modeling Cell Biology.- Model reduction for Stochastic Reaction Systems.- ZI-closure Scheme: A Method to Solve and Study Stochastic Reaction Networks.- Deterministic and Stochastic Becker-Dцring Equations: Past and Recent Mathematical Developments.- Coagulation-Fragmentation with a Finite Number of Particles: Models, Stochastic Analysis and Applications to Telomere Clustering and Viral Capsid Assembly.- A Review of Stochastic and Delay Simulation Approaches in both Time and Space in Computational Cell Biology.- Part IV: Diffusion Processes and Stochastic Modeling.- Recent Mathematical Models of Axonal Transport.- Stochastic Models for Evolving Cellular Populations of Mitochondria: Disease, Development, and Ageing.- Modeling and Stochastic Analysis of the Single Photon Response.- A Phenomenological Spatial Model for Macro-ecological Patterns in Species-rich Ecosystems.
Название: Statistical Inference in Stochastic Processes ISBN: 0367403072 ISBN-13(EAN): 9780367403072 Издательство: Taylor&Francis Рейтинг: Цена: 10104.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and statistical techniques in image analysis and processing, develops likelihood methods for inference about parameters that determine the drift and the jump mechanism of a di
Автор: Sastry N S Narasimha Et Al Название: Perspectives In Mathematical Science I: Probability And Statistics ISBN: 9814273627 ISBN-13(EAN): 9789814273626 Издательство: World Scientific Publishing Рейтинг: Цена: 13464.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A collection of invited articles by distinguished probabilists and statisticians on the occasion of the Platinum Jubilee Celebrations of the Indian Statistical Institute. It covers topics in probability and statistics, and offers a perspective of different areas of research, emphasizing the major challenging issues.
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