Böcker utgivna av Springer-Verlag New York Inc.

An ideal text for applied statisticians needing a standalone introduction to computational Bayesian statistics, this work by a renowned authority on the subject focuses on standard models backed up by real datasets. It includes an inclusive R (CRAN) package.

This volume offers a practical introduction to the use of neuroscience to teach second languages. It provides information on the relation between how the brain learns and how this can be used to construct classroom activities, evaluates methods, syllabi, approaches, etc.

Many experimental discoveries during the last decade, including heavy fermions, fractional quantum Hall effect, high temperature superconductivity, and quantum spin chains, are not readily accessible from the weak coupling point of view.

The aim of this book is to illustrate by significant special examples three aspects of the theory of Diophantine approximations: the formal relationships that exist between counting processes and the functions entering the theory;

A carefully written text, suitable as an introductory course for second or third year students. The main scope of the text guides students towards a critical understanding and handling of data sets together with the ensuing testing of hypotheses.

This book gathers thousands of up-to-date equations, formulas, tables, illustrations, and explanations into one invaluable volume. It includes over a thousand pages of mathematical material as well as chapters on probability, mathematical statistics, fuzzy logic, and neural networks.

Since the characterization of generators of C0 semigroups was established in the 1940s, semigroups of linear operators and its neighboring areas have developed into an abstract theory that has become a necessary discipline in functional analysis and differential equations.

This is the first English translation of Husserliana XXIII, the volume in the critical edition of Edmund Husserl's works that gathers together a rich array of posthumous texts on representational consciousness.

For more than half of the 20* century, psychologists sought to locate the causes of behaviour in individuals and tended to neglect the possibility of locating the psy chological in the social.

Bridges the gap between theoretical and computational aspects of prime numbersExercise sections are a goldmine of interesting examples, pointers to the literature and potential research projectsAuthors are well-known and highly-regarded in the field

This textbook provides undergraduate students with an introduction to the basic theoretical models of computability. Students who have already some experience with elementary discrete mathematics will find this a well-paced first course. Plenty of exercises are provided, ranging from the easy to the challenging.

Written for statisticians, computer scientists, geographers, researchers, and others interested in visualizing data. This book presents a foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems.

Covers theoretical questions including the extension of the formalism, as well as more practical ones such as computational issues. This book focuses on statistical signal processing, nonparametric curve estimation, random measures, limit theorems, learning theory and some applications at the fringe between Statistics and Approximation Theory.

This book provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Effort has been made to relate biological to statistical parameters throughout, and extensive examples are included to illustrate the arguments.

This is a comprehensive review of commutative algebra, from localization and primary decomposition through dimension theory, homological methods, free resolutions and duality, emphasizing the origins of the ideas and their connections with other parts of mathematics.

This book introduces the geometry of 3-D vision, that is, the reconstruction of 3-D models of objects from a collection of 2-D images. It details the classic theory of two view geometry and shows that a more proper tool for studying the geometry of multiple views is the so-called rank consideration of the multiple view matrix.

The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed.

Basic properties, homotopy classification, and characteristic classes of fibre bundles have become an essential part of graduate mathematical education for students in geometry and mathematical physics.

The study of "soft matter" materials with complex properties has raised a number of interesting problems in basic physics, biology, and materials science, all of which promise new and important technological applications.

This textbook, ideal for students and lecturers alike, is a systematic study of the qualitative and geometric theory of nonlinear differential equations and dynamical systems. It includes a thorough treatment of linear systems.

"This book is the first volume of a two-volume textbook for undergraduates and is indeed the crystallization of a course offered by the author at the California Institute of Technology to undergraduates without any previous knowledge of number theory.

This introduction to applied nonlinear dynamics and chaos places emphasis on teaching the techniques and ideas that will enable students to take specific dynamical systems and obtain some quantitative information about their behavior.

In many statistical applications, scientists have to analyze the occurrence of observed clusters of events in time or space. Scientists are especially interested in determining whether an observed cluster of events has occurred by chance if it is assumed that the events are distributed independently and uniformly over time or space.

Generalizability theory offers an extensive conceptual framework and a powerful set of statistical procedures for characterizing and quantifying the fallibility of measurements. The book provides a synthesis of those parts of the statistical literature that are directly applicable to generalizability theory.

This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. The book builds on recent developments, both at the foundational level and the computational level, to present a self-contained view.

The area of analysis and control of mechanical systems using differential geometry is flourishing. This book collects many results over the last decade and provides a comprehensive introduction to the area.

New edition of a well-known classic in the field; Previous edition sold over 6000 copies worldwide; Fully-worked examples; Many carefully selected problems

This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.

Since Markov decision processes can be viewed as a special noncompeti tive case of stochastic games, we introduce the new terminology Competi tive Markov Decision Processes that emphasizes the importance of the link between these two topics and of the properties of the underlying Markov processes.

The authors' novel approach to some interesting mathematical concepts - not normally taught in other courses - places them in a historical and philosophical setting.