24 x 17 cm. X, 250 pages. ClothISBN 3-11-017876-1
Series: de Gruyter Expositions in Mathematics 40
Subjects: Mathematics / Geometry and Topology
Language: English
to be published April 2005
Symplectic geometry is the geometry underlying Hamiltonian
dynamics, and symplectic mappings arise as time-1-maps of
Hamiltonian flows. The spectacular rigidity phenomena for
symplectic mappings discovered in the last two decades show that
certain things cannot be done by a symplectic mapping. For
instance, Gromov's famous "non-squeezing'' theorem states
that one cannot map a ball into a thinner cylinder by a
symplectic embedding. The aim of this book is to show that
certain other things can be done by symplectic mappings. This is
achieved by various elementary and explicit symplectic embedding
constructions, such as "folding", "wrapping'', and
"lifting''. These constructions are carried out in detail
and are used to solve some specific symplectic embedding problems.
The exposition is self-contained and addressed to students and
researchers interested in geometry or dynamics.
Contents
*
IRMA Lectures in Mathematics and Theoretical Physics Vol. 6
ISBN 3-03719-010-8
December 2004, 300 pages, softcover, 17.0 cm x 24.0 cm.
4
This book is about metric spaces of nonpositive curvature in the
sense of Busemann, that is, metric spaces whose distance function
satisfies a convexity condition. The book also contains a
systematic introduction to the theory of geodesics, as well as a
detailed presentation of some facets of convexity theory that are
useful in the study of nonpositive curvature.
The concepts and the techniques are illustrated by many examples
from classical hyperbolic geometry and from the theory of
Teichmuller spaces.
The book is useful for students and researchers in geometry,
topology and analysis.
ISBN: 0-471-73577-9
Paperback
536 pages
March 2005
The Wiley-Interscience Paperback Series consists of selected
books that have been made more accessible to consumers in an
effort to increase global appeal and general circulation. With
these new unabridged softcover volumes, Wiley hopes to extend the
lives of these works by making them available to future
generations of statisticians, mathematicians, and scientists.
"This is a nice book containing a wealth of information,
much of it due to the authors. . . . If an instructor designing
such a course wanted a textbook, this book would be the best
choice available. . . . There are many stimulating exercises, and
the book also contains an excellent index and an extensive list
of references."
?Technometrics
"[This] book should be read carefully by anyone who is
interested in dealing with statistical models in a realistic
fashion."
?American Scientist
Introducing concepts, theory, and applications, Robust Statistics
is accessible to a broad audience, avoiding allusions to high-powered
mathematics while emphasizing ideas, heuristics, and background.
The text covers the approach based on the influence function (the
effect of an outlier on an estimater, for example) and related
notions such as the breakdown point. It also treats the change-of-variance
function, fundamental concepts and results in the framework of
estimation of a single parameter, and applications to estimation
of covariance matrices and regression parameters.
ISBN: 0-471-55177-5
Hardcover
816 pages
April 2005
A comprehensive overview of experimental design at the advanced
level.
The development and introduction of new experimental designs in
the last fifty years has been quite staggering and was brought
about largely by an ever-widening field of applications. Design
and Analysis of Experiments, Volume 2: Advanced Experimental
Design is the second of a two-volume body of work that builds
upon the philosophical foundations of experimental design set
forth half a century ago by Oscar Kempthorne, and features the
latest developments in the field.
Volume 1: An Introduction to Experimental Design introduced
students at the MS level to the principles of experimental
design, including the groundbreaking work of R. A. Fisher and
Frank Yates, and Kempthorne's work in randomization theory with
the development of derived linear models. Design and Analysis of
Experiments, Volume 2 provides more detail about aspects of error
control and treatment design, with emphasis on their historical
development and practical significance, and the connections
between them. Designed for advanced-level graduate students and
industry professionals, this text includes coverage of:
* Incomplete block and row-column designs
* Symmetrical and asymmetrical factorial designs
* Systems of confounding
* Fractional factorial designs, including main effect plans
* Supersaturated designs
* Robust design or Taguchi experiments
* Lattice designs
* Crossover designs
In order to facilitate the application of text material to a
broad range of fields, the authors take a general approach to
their discussions. To aid in the construction and analysis of
designs, many procedures are illustrated using Statistical
Analysis System (SAS(r)) software.
ISBN: 0-470-09237-8
Hardcover
448 pages
July 2005
The use of Bayesian methods for the analysis of data has grown
substantially in areas as diverse as applied statistics,
psychology, economics and medical science. Bayesian Methods for
Categorical Data sets out to demystify modern Bayesian methods,
making them accessible to students and researchers alike.
Emphasizing the use of statistical computing and applied data
analysis, this book provides a comprehensive introduction to
Bayesian methods of categorical outcomes.
* Reviews recent Bayesian methodology for categorical outcomes (binary,
count and multinomial data).
* Considers missing data models techniques and non-standard
models (ZIP and negative binomial).
* Evaluates time series and spatio-temporal models for discrete
data.
* Features discussion of univariate and multivariate techniques.
* Provides a set of downloadable worked examples with documented
WinBUGS code, available from an ftp site.
The author's previous 2 bestselling titles provided a
comprehensive introduction to the theory and application of
Bayesian models. Bayesian Models for Categorical Data continues
to build upon this foundation by developing their application to
categorical, or discrete data - one of the most common types of
data available. The author's clear and logical approach makes the
book accessible to a wide range of students and practitioners,
including those dealing with categorical data in medicine,
sociology, psychology and epidemiology.
ISBN: 0-471-42027-1
Hardcover
544 pages
June 2005
Description
This text presents and describes methods for analysis of
longitudinal data, with a strong emphasis on application of these
methods to problems in the biomedical and behavioral sciences.
Applied Longitudinal Data Analysis is geared more toward users,
and not developers, of statistics. Specific statistical
procedures that the book will describe include: repeated measures
analysis of variance, multivariate analysis of variance for
repeated measures, random-effects regression models (RRM),
covariance-structure models, and generalized-estimating equations
(GEE) models.