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Large Deviations
Offers an introduction to large deviations. This book is divided into two parts: theory and applications. It presents basic large deviation theorems for i i d sequences, Markov sequences, and sequences with moderate dependence. It also includes an outline of general definitions and theorems.
Deviations
Collection of writings by Gayle S. Rubin, an American theorist and activist in feminist, lesbian and gay, queer, and sexuality studies since the 1970s.
Standard Deviations
Did you know that having a messy room will make you racist? Or that human beings possess the ability to postpone death until after important ceremonial occasions? Or that people live three to five years longer if they have positive initials, like ACE? All of these 'facts' have been argued with a straight face by researchers and backed up with reams of data and convincing statistics. As Nobel Prize-winning economist Ronald Coase once cynically observed, 'If you torture data long enough, it will confess.' Lying with statistics is a time-honoured con. In Standard Deviations, economics professor Gary Smith walks us through the various tricks and traps that people use to back up their own crackpo...
An Introduction to the Theory of Large Deviations
These notes are based on a course which I gave during the academic year 1983-84 at the University of Colorado. My intention was to provide both my audience as well as myself with an introduction to the theory of 1arie deviations • The organization of sections 1) through 3) owes something to chance and a great deal to the excellent set of notes written by R. Azencott for the course which he gave in 1978 at Saint-Flour (cf. Springer Lecture Notes in Mathematics 774). To be more precise: it is chance that I was around N. Y. U. at the time'when M. Schilder wrote his thesis. and so it may be considered chance that I chose to use his result as a jumping off point; with only minor variations. eve...
Large Deviations
The first four chapters of this volume are based on lectures given by Stroock at MIT in 1987. They form an introduction to the basic ideas of the theory of large deviations and make a suitable package on which to base a semester-length course for advanced graduate students with a strong background in analysis and some probability theory. A large selection of exercises presents important material and many applications. The last two chapters present various non-uniform results (Chapter 5) and outline the analytic approach that allows one to test and compare techniques used in previous chapters (Chapter 6).
Deviate
World-renowned neuroscientist Beau Lotto reveals the truths of human perception and devises a cognitive toolkit for how to succeed in a world of uncertainty. Perception is the foundation of human experience, but few of us understand how our own perception works. By revealing the startling truths about the brain and perception, Beau Lotto shows that the next big innovation is not a new technology: it is a new way of seeing. In his first major book, Beau Lotto draws on over a decade of pioneering research to show how our brains play tricks on us. With an innovative combination of case studies and optical- and perception-illusion exercises, DEVIATE will revolutionise the way you see the world. With this new understanding of how the brain works and its perceptive trickery, we can apply these insights to every aspect of life and work. DEVIATE is not just an engaging look into the neuroscience of thought, behaviour and creativity: it is a call to action, enlisting readers in their own journey of self-discovery.
Large Deviations and Idempotent Probability
In the view of many probabilists, author Anatolii Puhalskii's research results stand among the most significant achievements in the modern theory of large deviations. In fact, his work marked a turning point in the depth of our understanding of the connections between the large deviation principle (LDP) and well-known methods for establishing weak
Large Deviations Techniques and Applications
Large deviation estimates have proved to be the crucial tool required to handle many questions in statistics, engineering, statistial mechanics, and applied probability. Amir Dembo and Ofer Zeitouni, two of the leading researchers in the field, provide an introduction to the theory of large deviations and applications at a level suitable for graduate students. The mathematics is rigorous and the applications come from a wide range of areas, including electrical engineering and DNA sequences. The second edition, printed in 1998, included new material on concentration inequalities and the metric and weak convergence approaches to large deviations. General statements and applications were sharpened, new exercises added, and the bibliography updated. The present soft cover edition is a corrected printing of the 1998 edition.
Refined Large Deviation Limit Theorems
This is a developing area of modern probability theory, which has applications in many areas. This volume is devoted to the systematic study of results on large deviations in situations where Cramér's condition on the finiteness of exponential moments may not be satisfied
Entropy, Large Deviations, and Statistical Mechanics
From the reviews: "... Besides the fact that the author's treatment of large deviations is a nice contribution to the literature on the subject, his book has the virue that it provides a beautifully unified and mathematically appealing account of certain aspects of statistical mechanics. ... Furthermore, he does not make the mistake of assuming that his mathematical audience will be familiar with the physics and has done an admireable job of explaining the necessary physical background. Finally, it is clear that the author's book is the product of many painstaking hours of work; and the reviewer is confident that its readers will benefit from his efforts." D. Stroock in Mathematical Reviews 1985 "... Each chapter of the book is followed by a notes section and by a problems section. There are over 100 problems, many of which have hints. The book may be recommended as a text, it provides a completly self-contained reading ..." S. Pogosian in Zentralblatt für Mathematik 1986
