Stochastic modelling and applied probability - 9783642393624 - stochastic simulation and monte carlo methods: mathematical foundations of stochastic simulations: 68 di graham, carl; talay, denis (14 risultati)
Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Condizione: New. In English.
Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Lingua: Inglese
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Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Condizione: New. pp. 278.
Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners' aim to simulate more and more complex systems, and thus use random parameters as well…as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view. The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations.
Lingua: Inglese
Editore: Springer Berlin Heidelberg, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Da: moluna, Greven, Germaniamoluna
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Gebunden. Condizione: New.
Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 264 pages. 9.50x6.25x0.75 inches. In Stock.
Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer Berlin Heidelberg Jul 2013, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners' aim to simulate more and more complex systems, and thus use random par…ameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view. The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations. 276 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. 278 Illus.
Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 278.
Lingua: Inglese
Editore: Springer, Springer Gabler Jul 2013, 2013
Serie: Libro 27 di 30 - Stochastic Modelling and Applied Probability
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners¿ aim to simulate more and more complex systems, and thus use random paramet…ers as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view.The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 276 pp. Englisch.
