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Zustand: New. This textbook is an introduction to probability theory with the right balance between mathematical precision, probabilistic intuition, and concrete applications. It is intended for students with a calculus background, as well as for independent learners and.
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Hardcover. Zustand: new. Hardcover. The study of random growth models began in probability theory about 50 years ago, and today this area occupies a central place in the subject. The considerable challenges posed by these models have spurred the development of innovative probability theory and opened up connections with several other parts of mathematics, such as partial differential equations, integrable systems, and combinatorics. These models also have applications to fields such as computer science, biology, and physics.This volume is based on lectures delivered at the 2017 AMS Short Course ``Random Growth Models'', held January 2-3, 2017 in Atlanta, GA.The articles in this book give an introduction to the most-studied models; namely, first- and last-passage percolation, the Eden model of cell growth, and particle systems, focusing on the main research questions and leading up to the celebrated Kardar-Parisi-Zhang equation. Topics covered include asymptotic properties of infection times, limiting shape results, fluctuation bounds, and geometrical properties of geodesics, which are optimal paths for growth. Based on lectures delivered at the 2017 AMS Short Course Random Growth Models, held in 2017. The articles give an introduction to the most-studied models; first- and last-passage percolation, the Eden model of cell growth, and particle systems, focusing on the main research questions and leading up to the celebrated Kardar-Parisi-Zhang equation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Verlag: American Mathematical Society, US, 2015
ISBN 10: 0821875787 ISBN 13: 9780821875780
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In den WarenkorbHardback. Zustand: New. This is an introductory course on the methods of computing asymptotics of probabilities of rare events: the theory of large deviations. The book combines large deviation theory with basic statistical mechanics, namely Gibbs measures with their variational characterization and the phase transition of the Ising model, in a text intended for a one semester or quarter course.The book begins with a straightforward approach to the key ideas and results of large deviation theory in the context of independent identically distributed random variables. This includes Cramer's theorem, relative entropy, Sanov's theorem, process level large deviations, convex duality, and change of measure arguments.Dependence is introduced through the interactions potentials of equilibrium statistical mechanics. The phase transition of the Ising model is proved in two different ways: first in the classical way with the Peierls argument, Dobrushin's uniqueness condition, and correlation inequalities and then a second time through the percolation approach.Beyond the large deviations of independent variables and Gibbs measures, later parts of the book treat large deviations of Markov chains, the Gartner-Ellis theorem, and a large deviation theorem of Baxter and Jain that is then applied to a nonstationary process and a random walk in a dynamical random environment.The book has been used with students from mathematics, statistics, engineering, and the sciences and has been written for a broad audience with advanced technical training. Appendixes review basic material from analysis and probability theory and also prove some of the technical results used in the text.
Verlag: American Mathematical Society, 2018
ISBN 10: 1470435535 ISBN 13: 9781470435530
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Zustand: New. Based on lectures delivered at the 2017 AMS Short Course Random Growth Models , held in 2017. The articles give an introduction to the most-studied models first- and last-passage percolation, the Eden model of cell growth, and particle systems, focusing o.
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ISBN 10: 0821875787 ISBN 13: 9780821875780
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Gebunden. Zustand: New. Presents an introductory course on the methods of computing asymptotics of probabilities of rare events: the theory of large deviations. The book combines large deviation theory with basic statistical mechanics, namely Gibbs measures with their variational .
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In den WarenkorbHardback. Zustand: New. This is an introductory course on the methods of computing asymptotics of probabilities of rare events: the theory of large deviations. The book combines large deviation theory with basic statistical mechanics, namely Gibbs measures with their variational characterization and the phase transition of the Ising model, in a text intended for a one semester or quarter course.The book begins with a straightforward approach to the key ideas and results of large deviation theory in the context of independent identically distributed random variables. This includes Cramer's theorem, relative entropy, Sanov's theorem, process level large deviations, convex duality, and change of measure arguments.Dependence is introduced through the interactions potentials of equilibrium statistical mechanics. The phase transition of the Ising model is proved in two different ways: first in the classical way with the Peierls argument, Dobrushin's uniqueness condition, and correlation inequalities and then a second time through the percolation approach.Beyond the large deviations of independent variables and Gibbs measures, later parts of the book treat large deviations of Markov chains, the Gartner-Ellis theorem, and a large deviation theorem of Baxter and Jain that is then applied to a nonstationary process and a random walk in a dynamical random environment.The book has been used with students from mathematics, statistics, engineering, and the sciences and has been written for a broad audience with advanced technical training. Appendixes review basic material from analysis and probability theory and also prove some of the technical results used in the text.
Verlag: American Mathematical Society, 2018
ISBN 10: 1470435535 ISBN 13: 9781470435530
Sprache: Englisch
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Hardcover. Zustand: new. Hardcover. The study of random growth models began in probability theory about 50 years ago, and today this area occupies a central place in the subject. The considerable challenges posed by these models have spurred the development of innovative probability theory and opened up connections with several other parts of mathematics, such as partial differential equations, integrable systems, and combinatorics. These models also have applications to fields such as computer science, biology, and physics.This volume is based on lectures delivered at the 2017 AMS Short Course ``Random Growth Models'', held January 2-3, 2017 in Atlanta, GA.The articles in this book give an introduction to the most-studied models; namely, first- and last-passage percolation, the Eden model of cell growth, and particle systems, focusing on the main research questions and leading up to the celebrated Kardar-Parisi-Zhang equation. Topics covered include asymptotic properties of infection times, limiting shape results, fluctuation bounds, and geometrical properties of geodesics, which are optimal paths for growth. Based on lectures delivered at the 2017 AMS Short Course Random Growth Models, held in 2017. The articles give an introduction to the most-studied models; first- and last-passage percolation, the Eden model of cell growth, and particle systems, focusing on the main research questions and leading up to the celebrated Kardar-Parisi-Zhang equation. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.