Large Deviations for Stochastic Processes PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Large Deviations for Stochastic Processes PDF full book. Access full book title Large Deviations for Stochastic Processes by Jin Feng. Download full books in PDF and EPUB format.
Author: Jin Feng
Publisher: American Mathematical Soc.
ISBN: 0821841459
Category : Mathematics
Languages : en
Pages : 426
Get Book Here
Book Description
The book is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in the theory of weak convergence. Part 2 focuses on Markov processes in metric spaces. For a sequence of such processes, convergence of Fleming's logarithmically transformed nonlinear semigroups is shown to imply the large deviation principle in a manner analogous to the use of convergence of linear semigroups in weak convergence. Viscosity solution methods provide applicable conditions for the necessary convergence. Part 3 discusses methods for verifying the comparison principle for viscosity solutions and applies the general theory to obtain a variety of new and known results on large deviations for Markov processes. In examples concerning infinite dimensional state spaces, new comparison principles are de
Author: Jin Feng
Publisher: American Mathematical Soc.
ISBN: 0821841459
Category : Mathematics
Languages : en
Pages : 426
Get Book Here
Book Description
The book is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in the theory of weak convergence. Part 2 focuses on Markov processes in metric spaces. For a sequence of such processes, convergence of Fleming's logarithmically transformed nonlinear semigroups is shown to imply the large deviation principle in a manner analogous to the use of convergence of linear semigroups in weak convergence. Viscosity solution methods provide applicable conditions for the necessary convergence. Part 3 discusses methods for verifying the comparison principle for viscosity solutions and applies the general theory to obtain a variety of new and known results on large deviations for Markov processes. In examples concerning infinite dimensional state spaces, new comparison principles are de
Author: Alejandro D. de Acosta
Publisher: American Mathematical Soc.
ISBN: 0821890891
Category : Mathematics
Languages : en
Pages : 120
Get Book Here
Book Description
Author: Anatolii Puhalskii
Publisher: CRC Press
ISBN: 1420035800
Category : Business & Economics
Languages : en
Pages : 515
Get Book Here
Book Description
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
Author: Amir Dembo
Publisher: Springer Science & Business Media
ISBN: 3642033113
Category : Science
Languages : en
Pages : 409
Get Book Here
Book Description
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.
Author: Jin Feng
Publisher: American Mathematical Soc.
ISBN: 1470418703
Category : Mathematics
Languages : en
Pages : 426
Get Book Here
Book Description
The book is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in the theory of weak convergence. Part 2 focuses on Markov processes in metric spaces. For a sequence of such processes, convergence of Fleming's logarithmically transformed nonlinear semigroups is shown to imply the large deviation principle in a manner analogous to the use of convergence of linear semigroups in weak convergence. Viscosity solution methods provide applicable conditions for the necessary convergence. Part 3 discusses methods for verifying the comparison principle for viscosity solutions and applies the general theory to obtain a variety of new and known results on large deviations for Markov processes. In examples concerning infinite dimensional state spaces, new comparison principles are derived for a class of Hamilton-Jacobi equations in Hilbert spaces and in spaces of probability measures.
Author: Paul Dupuis
Publisher: John Wiley & Sons
ISBN: 1118165896
Category : Mathematics
Languages : en
Pages : 506
Get Book Here
Book Description
Applies the well-developed tools of the theory of weak convergenceof probability measures to large deviation analysis--a consistentnew approach The theory of large deviations, one of the most dynamic topics inprobability today, studies rare events in stochastic systems. Thenonlinear nature of the theory contributes both to its richness anddifficulty. This innovative text demonstrates how to employ thewell-established linear techniques of weak convergence theory toprove large deviation results. Beginning with a step-by-stepdevelopment of the approach, the book skillfully guides readersthrough models of increasing complexity covering a wide variety ofrandom variable-level and process-level problems. Representationformulas for large deviation-type expectations are a key tool andare developed systematically for discrete-time problems. Accessible to anyone who has a knowledge of measure theory andmeasure-theoretic probability, A Weak Convergence Approach to theTheory of Large Deviations is important reading for both studentsand researchers.
Author: S. R. S. Varadhan
Publisher: SIAM
ISBN: 0898711894
Category : Mathematics
Languages : en
Pages : 74
Get Book Here
Book Description
Many situations exist in which solutions to problems are represented as function space integrals. Such representations can be used to study the qualitative properties of the solutions and to evaluate them numerically using Monte Carlo methods. The emphasis in this book is on the behavior of solutions in special situations when certain parameters get large or small.
Author: Enzo Olivieri
Publisher: Cambridge University Press
ISBN: 9780521591638
Category : Mathematics
Languages : en
Pages : 540
Get Book Here
Book Description
Publisher Description
Author: O. V. Gulinsky
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110917807
Category : Mathematics
Languages : en
Pages : 192
Get Book Here
Book Description
No detailed description available for "Large Deviations for Discrete-Time Processes with Averaging".
Author: Robert G. Gallager
Publisher: Cambridge University Press
ISBN: 1107039754
Category : Business & Economics
Languages : en
Pages : 559
Get Book Here
Book Description
The definitive textbook on stochastic processes, written by one of the world's leading information theorists, covering both theory and applications.
