9781493995776 - analysis and approximation of rare events: representations and weak convergence methods: 94 (probability theory and stochastic modelling, 94) de budhiraja, amarjit; dupuis, paul (20 resultados)
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Editorial: Springer 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Editorial: Springer-Verlag New York Inc., US 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Editorial: Springer-Verlag New York Inc., New York 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Hardcover. Condición: new. Hardcover. This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. A feature of the book is the systematic use of variational representations for quantities of interest such as normalized logarithms of pro…babilities and expected values. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations. These features are illustrated though their application to a broad range of discrete and continuous time models, including stochastic partial differential equations, processes with discontinuous statistics, occupancy models, and many others. The tools used in the large deviation analysis also turn out to be useful in understanding Monte Carlo schemes for the numerical approximation of the same probabilities and expected values. This connection is illustrated through the design and analysis of importance sampling and splitting schemes for rare event estimation. The book assumes a solid background in weak convergence of probability measures and stochastic analysis, and is suitable for advanced graduate students, postdocs and researchers. This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Editorial: Springer 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Editorial: Springer-Verlag New York Inc., US 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Hardback. Condición: New. 2019 ed.
Idioma: Inglés
Editorial: Springer 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Idioma: Inglés
Editorial: Springer 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Editorial: Springer, Springer 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. A feature of the book is the systematic use of variational representations for quantities of interest… such as normalized logarithms of probabilities and expected values. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations. These features are illustrated though their application to a broad range of discrete and continuous time models, including stochastic partial differential equations, processes with discontinuous statistics, occupancy models, and many others. The tools used in the large deviation analysis also turn out to be useful in understanding Monte Carlo schemes for the numerical approximation of the same probabilities and expected values. This connection is illustrated through the design and analysis of importance sampling and splitting schemes for rare event estimation. The book assumes a solid background in weak convergence of probability measures and stochastic analysis, and is suitable for advanced graduate students, postdocs and researchers.
Idioma: Inglés
Editorial: Springer Verlag 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Hardcover. Condición: Brand New. 574 pages. 9.25x6.25x1.50 inches. In Stock.
Idioma: Inglés
Editorial: Springer 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Editorial: Springer-Verlag New York Inc., New York 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Hardcover. Condición: new. Hardcover. This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. A feature of the book is the systematic use of variational representations for quantities of interest such as normalized logarithms of pro…babilities and expected values. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations. These features are illustrated though their application to a broad range of discrete and continuous time models, including stochastic partial differential equations, processes with discontinuous statistics, occupancy models, and many others. The tools used in the large deviation analysis also turn out to be useful in understanding Monte Carlo schemes for the numerical approximation of the same probabilities and expected values. This connection is illustrated through the design and analysis of importance sampling and splitting schemes for rare event estimation. The book assumes a solid background in weak convergence of probability measures and stochastic analysis, and is suitable for advanced graduate students, postdocs and researchers. This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Editorial: Springer US Aug 2019 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. A feature of the book is the systematic use of variational representations for quanti…ties of interest such as normalized logarithms of probabilities and expected values. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations. These features are illustrated though their application to a broad range of discrete and continuous time models, including stochastic partial differential equations, processes with discontinuous statistics, occupancy models, and many others. The tools used in the large deviation analysis also turn out to be useful in understanding Monte Carlo schemes for the numerical approximation of the same probabilities and expected values. This connection is illustrated through the design and analysis of importance sampling and splitting schemes for rare event estimation. The book assumes a solid background in weak convergence of probability measures and stochastic analysis, and is suitable for advanced graduate students, postdocs and researchers. 596 pp. Englisch.
Idioma: Inglés
Editorial: Springer-Verlag New York Inc. 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 1134.
Idioma: Inglés
Editorial: Springer Verlag 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 574 pages. 9.25x6.25x1.50 inches. In Stock. This item is printed on demand.
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Editorial: Springer US 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Illustrates  the use of these methods using a wide variety of discrete and continuous time modelsTimely and important topic with significant developments over the last 15 yearsIncludes both theory an…d links with applications.
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Editorial: Springer, Springer Aug 2019 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems. A feature of the book is the systematic use of variational representations for quantities… of interest such as normalized logarithms of probabilities and expected values. By characterizing a large deviation principle in terms of Laplace asymptotics, one converts the proof of large deviation limits into the convergence of variational representations. These features are illustrated though their application to a broad range of discrete and continuous time models, including stochastic partial differential equations, processes with discontinuous statistics, occupancy models, and many others. The tools used in the large deviation analysis also turn out to be useful in understanding Monte Carlo schemes for the numerical approximation of the same probabilities and expected values. This connection is illustrated through the design and analysis of importance sampling and splitting schemes for rare event estimation. The book assumes a solid background in weak convergence of probability measures and stochastic analysis, and is suitable for advanced graduate students, postdocs and researchers.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 596 pp. Englisch.
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Editorial: Springer 2019
Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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Serie: Probability Theory and Stochastic Modelling, Libro 27 de 35. Libro 27 de 35 - Probability Theory and Stochastic Modelling
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