ISBN: 1584886129
Publication Date: 7/5/2006
Number of Pages: 328
Provides an introduction to analyzing multidimensional
categorical data using descriptive techniques
Presents necessary background material on statistical concepts
and data analysis methods
Discusses different types of analysis, including categorical,
descriptive, dual scaling, exhaustive, and optimal
Offers many numerical examples as well as case studies that
demonstrate the usefulness of the procedures
Includes actual worked examples from a range of application areas
including social and biological sciences
Features a straightforward approach suitable for newcomers to the
field as well as seasoned researchers
Quantification of categorical, or non-numerical, data is a
problem that scientists face across a wide range of disciplines.
Exploring data analysis in various areas of research, such as the
social sciences and biology, Multidimensional Nonlinear
Descriptive Analysis presents methods for analyzing categorical
data that are not necessarily sampled randomly from a normal
population and often involve nonlinear relations.
This reference not only provides an overview of multidimensional
nonlinear descriptive analysis (MUNDA) of discrete data, it also
offers new results in a variety of fields. The first part of the
book covers conceptual and technical preliminaries needed to
understand the data analysis in subsequent chapters. The next two
parts contain applications of MUNDA to diverse data types, with
each chapter devoted to one type of categorical data, a brief
historical comment, and basic skills peculiar to the data types.
The final part examines several problems and then concludes with
suggestions for future progress.
Covering both the early and later years of MUNDA research in the
social sciences, psychology, ecology, biology, and statistics,
this book provides a framework for potential developments in even
more areas of study.
Contents
Series: Texts in Statistical Science Series Volume: 70
ISBN: 1584885416
Publication Date: 8/22/2006
Number of Pages: 472
Presents an overview of computer-intensive statistical methods
and applications in biology
Covers a wide range of methods including bootstrap, Monte Carlo,
ANOVA, regression, and Bayesian
Features a clear, accessible style that makes it easy for
biologists, researchers, and students to understand the methods
discussed
Provides information on computer programs and packages to
implement calculations
Includes a large number of real, up-to-date examples from a range
of disciplines, particularly in the biological sciences
Contains summaries and exercises for each chapter, making it
suitable for courses and self-study
Modern computer-intensive statistical methods play a key role in
solving many problems across a wide range of scientific
disciplines. This new edition of the bestselling Randomization,
Bootstrap and Monte Carlo Methods in Biology illustrates the
value of a number of these methods with an emphasis on biological
applications.
This textbook focuses on three related areas in computational
statistics: randomization, bootstrapping, and Monte Carlo methods
of inference. The author emphasizes the sampling approach within
randomization testing and confidence intervals. Similar to
randomization, the book shows how bootstrapping, or resampling,
can be used for confidence intervals and tests of significance.
It also explores how to use Monte Carlo methods to test
hypotheses and construct confidence intervals.
New to the Third Edition
* Updated information on regression and time series analysis,
multivariate methods, survival and growth data as well as
software for computational statistics
* References that reflect recent developments in methodology and
computing techniques
* Additional references on new applications of computer-intensive
methods in biology
Providing comprehensive coverage of computer-intensive
applications while also offering data sets online, Randomization,
Bootstrap and Monte Carlo Methods in Biology, Third Edition
supplies a solid foundation for the ever-expanding field of
statistics and quantitative analysis in biology.
Contents
Series: Discrete Mathematics and Its Applications Volume: 41
ISBN: 1584886188
Publication Date: 9/7/2006
Number of Pages: 424
Includes new background material on number theory and complexity
theory
Contains two new application chapters covering such topics as
electronic mail, network security, and biometrics
Features expanded and updated exercise sets
Provides additional information on cryptanalysis
Continuing a best-selling tradition, An Introduction to
Cryptography, Second Edition features all of the requisite
background material on number theory and algorithmic complexity,
includes a historical look at the field, and offers updated and
expanded exercise sets. In addition to updates throughout the
text, this edition includes two new chapters on current and
future applications that cover such topics as electronic mail,
internet security, protocol layers and SSL, firewalls, client-server
model and cookies, network security, wireless security, smart
cards, and biometrics. The text also provides additional
information on cryptanalysis and primality testing as well as
appendices on DES and primitive roots.
Table of Contents
Basics of Cryptography. DES and AES. Public-Key Cryptosystems.
Primality Testing. Factoring. Electronic Mail and Internet
Security. Applications and the Future. Advanced Topics.
In print, 2006
ISBN 90 6764 457 9
Hardback (xviii, 572 pp.)
This course and reference book develops theoretical mechanics
within the modern framework of differential geometry.
Foundations of differential geometry recalled in a rigorous and
practical way as an unavoidable prerequisite make the work
autonomous. Manifolds, tensors, exterior algebra, Lie derivative,
Lie algebra, integration of forms, Riemannian geometry, and more
refer to a previous author's book. Since manifold symplectic
structure, canonical forms, brackets, etc. concern modern
mechanics, symplectic geometry is an 'interlinking field'.
Lagrangian and Hamiltonian formalisms, with their own spaces and
functions, start mechanics where fundamental principles, etc. are
clearly situated given didactic comparisons, numerous
diagrams,figures and solved exercises, as well as Hamilton-Jacobi
theory, perturbations, stability, qualitative dynamics.
Statistical mechanics, celestial mechanics, etc., also a fluid-dynamical
system , an original method with Fourier transforms deserve
research.
Readership: Professors, researchers, and 3rd -4th years students
concerned in mathematics (differential geometry, tensor analysis),
mechanics (theoretical, statistical), physics and engineering.
Anyone wishing to acquire insight into mathematical methods of
modern physics.
Yves R. Talpaert, Ph.D. (1974) in Science, Brussels University
where he taught mathematics. A past Professor of mathematics-mechanics
at several universities in Africa, he is a French author of books
on mechanics, geometry, and of papers on stellar dynamics.