ISBN: 978-0-470-12990-6
Hardcover
384 pages
February 2009
Robust Statistics, Second Edition includes four new chapters on the following topics: robust tests; small sample asymptotics; breakdown point; and Bayesian robustness. A new section on time series has also been included. The first edition of this book was the first systematic, book-length treatment of robust statistics. The book begins with a general introduction and the formal mathematical background behind qualitative and quantitative robustness. A solid foundation of robust statistics for both the theoretical and the applied statistician is provided. The book successfully reorganizes, summarizes, and extends information that has been available in part thus far. Concepts are stressed throughout rather than mathematical completeness, and selected numerical algorithms for computing robust estimates, as well as convergence proofs, are provided. Quantitative robustness information for a variety of estimates is contained within tables throughout.
ISBN: 978-0-470-29088-0
Hardcover
640 pages
February 2009
This comprehensive resource provides the algorithmic methods and state-of-the-art tools to successfully visualize statistical data. The coverage offers insight into underlying processes of density estimation, emphasizing use of visualization tools rather than only the theoretical concepts of classification and regression. The book is highly interactive in nature, as all figures and experiments can be reproduced via the two R software packages used throughout and available on a related Web site. Over 200 illustrations depict the discussed visualizations and Examples sections, making this both an dynamic text for students and a working reference for professionals.
Series: Understanding Complex Systems
2009, XII, 477 p. 448 illus., Hardcover
ISBN: 978-3-540-85631-3
Due: January 20, 2009
This edited book is aimed at interdisciplinary, device-oriented, applications of nonlinear science theory and methods in complex systems. In particular, applications directed to nonlinear phenomena with space and time characteristics. Examples include: complex networks of magnetic sensor systems, coupled nano-mechanical oscillators, nano-detectors, microscale devices, stochastic resonance in multi-dimensional chaotic systems, biosensors, and stochastic signal quantization. "applications of nonlinear dynamics: model and design of complex systems" brings together the work of scientists and engineers that are applying ideas and methods from nonlinear dynamics to design and fabricate complex systems.
Researchers, engineers, graduate students in applied nonlinear dynamics, including stochastic resonance
Series: Springer Monographs in Mathematics
Originally published in the series: Perpectives Mathematical Logic
2nd ed. 2003. Corr. 2nd printing, 2009, XXII, 536 p., Softcover
ISBN: 978-3-540-88866-6
Due: December 5, 2008
About this book The theory of large cardinals is currently a broad mainstream of modern set theory, the main area of investigation for the analysis of the relative consistency of mathematical propositions and possible new axioms for mathematics. The first of a projected multi-volume series, this book provides a comprehensive account of the theory of large cardinals from its beginnings and some of the direct outgrowths leading to the frontiers of contempory research. A "genetic" approach is taken, presenting the subject in the context of its historical development. With hindsight the consequential avenues are pursued and the most elegant or accessible expositions given. With open questions and speculations provided throughout the reader should not only come to appreciate the scope and coherence of the overall enterpreise but also become prepared to pursue research in several specific areas by studying the relevant sections.
Researchers and graduate students in set theory, including set-theoretic topology
infinitary combinatorics
large cardinals
new axioms for set theory
relative consistency results
set theory
Series: Geometry and Computing , Vol. 4
2009, Approx. 400 p., Hardcover
ISBN: 978-3-540-89067-6
Due: December 4, 2008
The application of geometric algebra to the engineering sciences is a young, active subject of research. The promise of this field is that the mathematical structure of geometric algebra together with its descriptive power will result in intuitive and more robust algorithms.
This book examines all aspects essential for a successful application of geometric algebra: the theoretical foundations, the representation of geometric constraints, and the numerical estimation from uncertain data. Formally, the book consists of two parts: theoretical foundations and applications. The first part includes chapters on random variables in geometric algebra, linear estimation methods that incorporate the uncertainty of algebraic elements, and the representation of geometry in Euclidean, projective, conformal and conic space. The second part is dedicated to applications of geometric algebra, which include uncertain geometry and transformations, a generalized camera model, and pose estimation.
Graduate students, scientists, researchers and practitioners will benefit from this book. The examples given in the text are mostly recent research results, so practitioners can see how to apply geometric algebra to real tasks, while researchers note starting points for future investigations. Students will profit from the detailed introduction to geometric algebra, while the text is supported by the author's visualization software, CLUCalc, freely available online, and a website that includes downloadable exercises, slides and tutorials.