
Large Deviations for Markov Chains by Alejandro D De Acosta
This book studies the large deviations for empirical measures and vector-valued additive functionals of Markov chains with general state space. Under suitable recurrence conditions, the ergodic theorem for additive functionals of a Markov chain asserts the almost sure convergence of the averages of a real or vector-valued function of the chain to the mean of the function with respect to the invariant distribution. In the case of empirical measures, the ergodic theorem states the almost sure convergence in a suitable sense to the invariant distribution. The large deviation theorems provide precise asymptotic estimates at logarithmic level of the probabilities of deviating from the preponderant behavior asserted by the ergodic theorems.-
The Geometry of Fractal Sets
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Riemannian Geometry
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Miniquaternion Geometry
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The Geometry of Total Curvature on Complete Open Surfaces
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Metric Spaces
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Birational Geometry and Manin's Conjecture
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Coherence in Three-Dimensional Category Theory
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Dilation and Model Theory for Pairs of Commuting Contraction Operators
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The Direct Method in Soliton Theory
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Matrix Positivity
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Rigidity in Higher Rank Abelian Group Actions: Volume 1, Introduction and Cocycle Problem
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Topics in Critical Point Theory
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Category and Measure
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The Mathieu Groups
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Modern Approaches to the Invariant-Subspace Problem
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Frobenius Manifolds and Moduli Spaces for Singularities
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Group Cohomology and Algebraic Cycles
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Permutation Group Algorithms
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Nonlinear Perron–Frobenius Theory
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Abelian Varieties, Theta Functions and the Fourier Transform
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Matrices of Sign-Solvable Linear Systems
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The Cube-A Window to Convex and Discrete Geometry
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The Large Sieve and its Applications
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Combinatorics of Minuscule Representations
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Polynomials and Vanishing Cycles
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Restricted Orbit Equivalence for Actions of Discrete Amenable Groups
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Metric Diophantine Approximation on Manifolds
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Applications of Diophantine Approximation to Integral Points and Transcendence
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An Introduction to Homotopy Theory
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Linear and Projective Representations of Symmetric Groups
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Dependence with Complete Connections and its Applications
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Fixed Point Theory and Applications
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Justification Logic
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Synthetic Geometry of Manifolds
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Dynamical Systems and Semisimple Groups
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Distribution Modulo One and Diophantine Approximation
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The Levy Laplacian
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Sets of Multiples
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Period Domains over Finite and p-adic Fields
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Levy Processes in Lie Groups
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Character Sums with Exponential Functions and their Applications
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Poincare Duality Algebras, Macaulay's Dual Systems, and Steenrod Operations
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Quasi-Frobenius Rings
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The Covering Property Axiom, CPA
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Ridge Functions
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Jordan Structures in Geometry and Analysis
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Typical Dynamics of Volume Preserving Homeomorphisms
'This is a treatise on the large deviations for the empirical measure (and additive functionals) of Markov chainsStructural assumptions are kept to a minimum, and great care is taken to separately obtain upper and lower bounds (which under appropriate conditions are shown to be equal). This book summarizes the author's work over the last 40 years and contains a plethora of new, sharpest in its class, results.' Ofer Zeitouni, Weizmann Institute, Israel
'This is a wonderful book. For four decades, Alejandro de Acosta's work in large deviations has been characterized by both its elegance and generality. Large Deviations for Markov Chains synthesizes, refines, and advances the current state of the field in a treatment that is at once rigorous and readable. It belongs on the bookshelf of any mathematician interested in the current state of the subject.' Sandy L. Zabell, Northwestern University
'This is an excellent book, by a top expert in the field, on large deviations for Markov chains in a very general setting. It is a valuable resource for graduate students learning the subject and for researchers in probability theory, statistical mechanics, statistics, engineering, and the sciences.' Firas Rassoul-Agha, University of Utah
'The theory of large deviations is an important way to understand many mathematical and physical models. This book covers the fascinating topic of large deviations for empirical measures and additive functionals of Markov chains with general state space, a subject on which the author is a leading expert who has made crucial contributions. Markov chains represent a large class of stochastic models with a wide spectrum of behaviors. It is remarkable that any universal results, like the ones given in the book, can be formulated for such a large family. It is equally remarkable that the book develops a sharp link between the large deviations and the degree of recurrence of Markov chains. The book does a superb job of clarification, comparison and identification of the rate functions that govern the large deviations.' Xia Chen, University of Tennessee
'This is a wonderful book. For four decades, Alejandro de Acosta's work in large deviations has been characterized by both its elegance and generality. Large Deviations for Markov Chains synthesizes, refines, and advances the current state of the field in a treatment that is at once rigorous and readable. It belongs on the bookshelf of any mathematician interested in the current state of the subject.' Sandy L. Zabell, Northwestern University
'This is an excellent book, by a top expert in the field, on large deviations for Markov chains in a very general setting. It is a valuable resource for graduate students learning the subject and for researchers in probability theory, statistical mechanics, statistics, engineering, and the sciences.' Firas Rassoul-Agha, University of Utah
'The theory of large deviations is an important way to understand many mathematical and physical models. This book covers the fascinating topic of large deviations for empirical measures and additive functionals of Markov chains with general state space, a subject on which the author is a leading expert who has made crucial contributions. Markov chains represent a large class of stochastic models with a wide spectrum of behaviors. It is remarkable that any universal results, like the ones given in the book, can be formulated for such a large family. It is equally remarkable that the book develops a sharp link between the large deviations and the degree of recurrence of Markov chains. The book does a superb job of clarification, comparison and identification of the rate functions that govern the large deviations.' Xia Chen, University of Tennessee
Alejandro D. de Acosta is Professor Emeritus in the Department of Mathematics, Applied Mathematics and Statistics at Case Western Reserve University. He has taught at the University of California at Berkeley, Massachusetts Institute of Technology, Universidad Nacional de La Plata and Universidad Nacional de Buenos Aires (Argentina), Instituto Venezolano de Investigaciones Científicas, University of Wisconsin–Madison, and, since 1983, at Case Western Reserve University. He is a Fellow of the Institute of Mathematical Statistics, and has served on the editorial boards of the Annals of Probability and the Journal of Theoretical Probability. He has published research papers in a number of areas of Probability Theory.
| SKU | Unavailable |
| ISBN 13 | 9781316511893 |
| ISBN 10 | 1316511898 |
| Title | Large Deviations for Markov Chains |
| Author | Alejandro D De Acosta |
| Series | Cambridge Tracts In Mathematics |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Cambridge University Press |
| Year published | 2022-10-27 |
| Number of pages | 230 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |














































