Описание: Exploiting the old maxim that "a picture is worth a thousand words," scientific visualization may be defined as the transformation of numerical scientific data into informative graphical displays. It introduces a nonverbal model into subdisciplines that hitherto employed mostly or only mathematical or verbal-conceptual models. The focus of this monograph is on how scientific visualization can help revolutionize the manner in which the tendencies for (dis)similar numerical values to cluster together in location on a map are explored and analyzed, affording spatial data analyses that are better understood, presented, and used. In doing so, the concept known as spatial autocorrelation - which characterizes these tendencies and is one of the key features of georeferenced data, or data tagged to the earth's surface - is further de-mystified. This self-correlation arises from relative locations in geographic space.
Автор: Lakhdar Aggoun Название: Measure Theory and Filtering ISBN: 0521838037 ISBN-13(EAN): 9780521838030 Издательство: Cambridge Academ Рейтинг: Цена: 7708 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus based probability theory. As conditional expectation is the key concept, the correct setting for filtering theory is that of a probability space. Graduate engineers, mathematicians and those working in quantitative finance wishing to use filtering techniques will find in the first half of this book an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion. Exercises are included. The book then provides an excellent users’ guide to filtering: basic theory is followed by a thorough treatment of Kalman filtering, including recent results which extend the Kalman filter to provide parameter estimates. These ideas are then applied to problems arising in finance, genetics and population modelling in three separate chapters, making this a comprehensive resource for both practitioners and researchers.
Автор: Elworthy Название: The Geometry of Filtering ISBN: 3034601751 ISBN-13(EAN): 9783034601757 Издательство: Springer Рейтинг: Цена: 5224 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The geometry used in this book is that determined by a map of one space N onto another, M, mapping a diffusion process, or operator, on N to one on M. That geometry is considered in situations of geometric, stochastic analytic or filtering interest.
Описание: This book offers an analytical rather than measure-theoretical approach to the derivation of the partial differential equations of nonlinear filtering theory. The basis for this approach is the discrete numerical scheme used in Monte-Carlo simulations of stochastic differential equations and Wiener's associated path integral representation of the transition probability density. Furthermore, it presents analytical methods for constructing asymptotic approximations to their solution and for synthesizing asymptotically optimal filters. It also offers a new approach to the phase tracking problem, based on optimizing the mean time to loss of lock. The book is based on lecture notes from a one-semester special topics course on stochastic processes and their applications that the author taught many times to graduate students of mathematics, applied mathematics, physics, chemistry, computer science, electrical engineering, and other disciplines. The book contains exercises and worked-out examples aimed at illustrating the methods of mathematical modeling and performance analysis of phase trackers.
Автор: S?rkk? Название: Bayesian Filtering and Smoothing ISBN: 1107619289 ISBN-13(EAN): 9781107619289 Издательство: Cambridge Academ Рейтинг: Цена: 3565 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications and medicine. This compact, informal introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. Readers learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how state-of-the-art Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book's practical and algorithmic approach assumes only modest mathematical prerequisites. Examples include Matlab computations, and the numerous end-of-chapter exercises include computational assignments. Matlab code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.
Автор: S?rkk? Название: Bayesian Filtering and Smoothing ISBN: 110703065X ISBN-13(EAN): 9781107030657 Издательство: Cambridge Academ Рейтинг: Цена: 9202 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications and medicine. This compact, informal introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. Readers learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how state-of-the-art Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book's practical and algorithmic approach assumes only modest mathematical prerequisites. Examples include Matlab computations, and the numerous end-of-chapter exercises include computational assignments. Matlab code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.
Автор: Laird Название: The fundamentals of modern statistical genetics ISBN: 1441973370 ISBN-13(EAN): 9781441973375 Издательство: Springer Рейтинг: Цена: 8881 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel’s first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.
Описание: This timely and synoptic text contains the essentials of queueing networks, from the classical product-form theory to the more recent developments such as diffusion and fluid limits, stochastic comparisons, stability, dynamic scheduling, and optimization.
Описание: Conventional statistical methods have a very serious flaw. They routinely miss differences among groups or associations among variables that are detected by more modern techniques - even under very small departures from normality. Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable. Improved methods have been derived, but they are far from obvious or intuitive based on the training most researchers receive. Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods. Without assuming any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand. The emphasis is on verbal and graphical descriptions of concepts. Part II describes modern methods that address the problems covered in Part I. Using data from actual studies, many examples are included to illustrate the practical problems with conventional procedures and how more modern methods can make a substantial difference in the conclusions reached in many areas of statistical research.Rand Wilcox is a professor of psychology at the University of Southern California. He is a fellow of the Royal Statistical Society and the American Psychological Society. Dr. Wilcox currently serves as an associate editor of Computational Statistics & Data Analysis and Psychometrika. He has published over 165 articles in a wide range of statistical journals and he is the author of three other books on statistics.|ВїThe volume is a jewel of direct explanations and information necessary for a good understanding of analysis of data, aimed at ordinary researchers who must try to present reasonable interpretable accounts of their data or judge when to abandon a particular strategy..."|- Perceptual and Motor Skills, 2002
Автор: Aggoun Название: Measure Theory and Filtering ISBN: 1107410711 ISBN-13(EAN): 9781107410718 Издательство: Cambridge Academ Рейтинг: Цена: 4600 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book was published in 2004. The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus-based probability theory. As conditional expectation is the key concept, the correct setting for filtering theory is that of a probability space. Graduate engineers, mathematicians and those working in quantitative finance wishing to use filtering techniques will find in the first half of this book an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion. Exercises are included. The book then provides an excellent users' guide to filtering: basic theory is followed by a thorough treatment of Kalman filtering, including recent results which extend the Kalman filter to provide parameter estimates. These ideas are then applied to problems arising in finance, genetics and population modelling in three separate chapters, making this a comprehensive resource for both practitioners and researchers.
Автор: Fanbiao Li; Peng Shi; Ligang Wu Название: Control and Filtering for Semi-Markovian Jump Systems ISBN: 3319471988 ISBN-13(EAN): 9783319471983 Издательство: Springer Рейтинг: Цена: 13672 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents up-to-date research developments and novel methodologies on semi-Markovian jump systems (S-MJS). It presents solutions to a series of problems with new approaches for the control and filtering of S-MJS, including stability analysis, sliding mode control, dynamic output feedback control, robust filter design, and fault detection. A set of newly developed techniques such as piecewise analysis method, positively invariant set approach, event-triggered method, and cone complementary linearization approaches are presented. Control and Filtering for Semi-Markovian Jump Systems is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.
Автор: Bhar Ramaprasad Название: Stochastic Filtering With Applications In Finance ISBN: 9814304859 ISBN-13(EAN): 9789814304856 Издательство: World Scientific Publishing Рейтинг: Цена: 11274 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Suitable for graduate level courses on stochastic modeling, this title does not intend to give a complete mathematical treatment of different stochastic filtering approaches, but rather to describe them in simple terms and illustrate their application with real historical data for problems normally encountered in these disciplines.
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