Series: Modern Birkhauser Classics
Originally published as a monograph
2nd ed. 1993. 2nd printing, 2008, Approx. 280 p. 5 illus., Softcover
ISBN: 978-0-8176-4774-2
About this book
Beautifully written articles from three great modern mathematicians
Ideas provoke thought and debate
Provides a source for supplemental reading for almost any math class
This is a volume of essays and reviews that delightfully explore mathematics in all its moods ? from the light and the witty, and humorous to serious, rational, and cerebral. Topics include: logic, combinatorics, statistics, economics, artificial intelligence, computer science, and applications of mathematics broadly. You will also find history and philosophy covered, including discussion of the work of Ulam, Kant, Heidegger among others.
Table of contents
Preface.- Acknowledgements.- Discrete thoughts.- Mathematics: Tensions.- The Pernicious Influence of Mathematics on Science.- Statistics.- Statistics and Its History.- Combinatorics.- Computer Science.- Mathematics: Trends.- The Future of Computer Science.- Economics, Mathematical and Empirical.- Complicating Mathematics.- Mathematics and Its History.- Academic Responsibility.- Husserl and the Reform of Logic.- Husserl.- Artificial Intelligence.- Computing and Its History.- Will Computers Replace Humans?.- Computer-Aided Instruction.- Misreading the History of Mathematics.- The Wonderful World of Uncle Stan.- Ulam.- Kant.- Heidegger.- Doing Away with Science.- More Discrete Thoughts
Series: Springer Series in Statistics
2008, XII, 476 p., Hardcover
ISBN: 978-0-387-74977-8
Due: February 2008
About this book
This book provides a self-contained, linear, and unified introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. The targeted audience includes statisticians, biostatisticians, and other researchers with a background in mathematical statistics who have an interest in learning about and doing research in empirical processes and semiparametric inference but who would like to have a friendly and gradual introduction to the area. The book can be used either as a research reference or as a textbook. The level of the book is suitable for a second year graduate course in statistics or biostatistics, provided the students have had a year of graduate level mathematical statistics and a semester of probability.
The book consists of three parts. The first part is a concise overview of all of the main concepts covered in the book with a minimum of technicalities. The second and third parts cover the two respective main topics of empirical processes and semiparametric inference in depth. The connections between these two topics is also demonstrated and emphasized throughout the text. Each part has a final chapter with several case studies that use concrete examples to illustrate the concepts developed so far. The last two parts also each include a chapter which covers the needed mathematical preliminaries. Each main idea is introduced with a non-technical motivation, and examples are given throughout to illustrate important concepts. Homework problems are also included at the end of each chapter to help the reader gain additional insights.
Michael R. Kosorok is Professor and Chair, Department of Biostatistics, and Professor, Department of Statistics and Operations Research, at the University of North Carolina at Chapel Hill. His research has focused on the application of empirical processes and semiparametric inference to statistics and biostatistics. He is a Fellow of both the American Statistical Association and the Institute of Mathematical Statistics. He is an Associate Editor of the Annals of Statistics, Electronic Journal of Statistics, International Journal of Biostatistics, Statistics and Probability Letters, and Statistics Surveys.
Table of contents
Introduction.- An Overview of The Empirical Processes.- Overview of Semiparametric Inference.- Case Studies I.- Introduction to Empirical Processes.- Preliminiaries for Empirical Processes.- Stochastic Convergence.- Empirical Process Methods.- Entropy Calculations.- Bootstrapping Empirical Processes.- Additional Empirical Process Results.- The Functional Delta Method.- Z-Estimators.- M-Estimators.- Case Studies II.- Introduction To Semiparametric Inference.- Seimparametric Models and Efficiency.- Efficient Inference for Fininte-Dimensional Parameters.- Efficient Inference for Infinite-Dimensional Parameters.- Semiparametric M-Estimators.- Case Studies III.
Series: Modern Birkhauser Classics
Originally published as a monograph
2nd ed. 1999. 2nd printing, 2008, Approx. 235 p. 45 illus., Softcover
ISBN: 978-0-8176-4778-0
Due: January 2008
About this book
Details a biography of one of the most important mathematicians in history, and an influential figure in the fields of philosophy and physics
Great companion text to a history of geometry course
This significantly expanded second edition of Riemann, Topology, and Physics combines a fascinating account of the life and work of Bernhard Riemann with a lucid discussion of current interaction between topology and physics. The author, a distinguished mathematical physicist, takes into account his own research at the Riemann archives of Gottingen University and developments over the last decade that connect Riemann with numerous significant ideas and methods reflected throughout contemporary mathematics and physics.
Special attention is paid in part one to results on the Riemann?Hilbert problem and, in part two, to discoveries in field theory and condensed matter such as the quantum Hall effect, quasicrystals, membranes with nontrivial topology, "fake" differential structures on 4-dimensional Euclidean space, new invariants of knots and more. In his relatively short lifetime, this great mathematician made outstanding contributions to nearly all branches of mathematics; today Riemannfs name appears prominently throughout the literature.
Table of contents
Preface to the Second Edition.- Preface to the First Edition.- From the Introduction to the First Edition.- Acknowledgements.- Bernhard Riemann.- Topological Themes in Contemporary Physics.- Index.
Series: Modern Birkhauser Classics
Reprint of the 1989 ed., 2008, XII, 166 p. 32 illus., Softcover
ISBN: 978-0-8176-4762-9
Due: February 2008
About this textbook
A more affordable version of a classic text, Gives a great introduction to logic for those with a computer science concentration, Perfect for a companion text to a undergraduate computer science class
This book introduces the notions and methods of formal logic from a computer science standpoint, covering propositional logic, predicate logic, and foundations of logic programming. It presents applications and themes of computer science research such as resolution, automated deduction, and logic programming in a rigorous but readable way.
Table of contents
Introduction.- Propositional Logic.- Predicate Logic.- Logic Programming.- Bibliography.- Table of Notations.- Index
Series: Modern Birkhauser Classics
Softcover reprint of the 1996 ed., 2008, XIV, 218 p. 30 illus., Softcover
ISBN: 978-0-8176-4760-5
Due: February 2008
About this textbook
An affordable new softcover edition of a bestselling text
Good undergraduate introduction to programming course, especially one which is mathematically motivated
May also be used as a textbook in a graduate course on the analysis of algorithms and/or compiler construction
The gproblem and solutionh style makes the reader think through the programming process, making the book ideal for students in the classroom setting or for self study
Algorithms and Programming is primarily intended for a first-year undergraduate course in programming. It is structured in a problem-solution format that requires the student to think through the programming process, thus developing an understanding of the underlying theory. Although the author assumes some moderate familiarity with programming constructs, the book is easily readable by a student taking a basic introductory course in computer science. In addition, the more advanced chapters make the book useful for a course at the graduate level in the analysis of algorithms and/or compiler construction.
Each chapter is more or less independent, containing classical and well-known problems supplemented by clear and in-depth explanations. The material covered includes such topics as combinatorics, sorting, searching, queues, grammar and parsing, selected well-known algorithms and much more. Students and teachers will find this both an excellent text for learning programming and a source of problems for a variety of courses.
Table of contents
Variables, expressions, assignments.- Generation of combinatorial objects.- Tree traversal (backtracking).- Sorting.- Finite-state algorithms in text processing.- Data types.- Recursion.- Recursive and nonrecursive programs.- Graph algorithms.- Pattern matching.- Set representation. Hashing.- Sets, trees, balanced trees.-Context-free grammar.- Left-to-right parsing (LR).- further reading