stochastic infinite dimensional analysis (35 Ergebnisse)

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Interest Rate Models: an Infinite Dimensional Stochastic Analysis Perspective studies the mathematical issues that arise in modeling the interest rate term structure. These issues are approached by casting the interest rate models as stochastic evolution equations in infinite dimensional function spaces. The book is comprised of three parts. Part I is a crash course on interest rates, including a statistical analysis of the data and an introduction to some popular interest rate models. Part II is a self-contained introduction to infinite dimensional stochastic analysis, including SDE in Hilbert spaces and Malliavin calculus. Part III presents some recent results in interest rate theory, including finite dimensional realizations of HJM models, generalized bond portfolios, and the ergodicity of HJM models.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Interest Rate Models: an Infinite Dimensional Stochastic Analysis Perspective studies the mathematical issues that arise in modeling the interest rate term structure. These issues are approached by casting the interest rate models as stochastic evolution equations in infinite dimensional function spaces. The book is comprised of three parts. Part I is a crash course on interest rates, including a statistical analysis of the data and an introduction to some popular interest rate models. Part II is a self-contained introduction to infinite dimensional stochastic analysis, including SDE in Hilbert spaces and Malliavin calculus. Part III presents some recent results in interest rate theory, including finite dimensional realizations of HJM models, generalized bond portfolios, and the ergodicity of HJM models.

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Couverture souple. Zustand: Bon. Edition originale. Sous la direction de S. Albeverio. Pitman advanced publishing program, Research in mathematics (124), 1985. In-8 broché, 244pp. Couverture légèrement défraichie.

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Taschenbuch. Zustand: Neu. Neuware -This volumepresents a collection of papers covering applications from a wide range ofsystems with infinitely many degrees of freedom studied using techniques fromstochastic and infinite dimensional analysis, e.g. Feynman path integrals, thestatistical mechanics of polymer chains, complex networks, and quantum fieldtheory. Systems of infinitely many degrees of freedom create their particularmathematical challenges which have been addressed by different mathematicaltheories, namely in the theories of stochastic processes, Malliavin calculusand especially white noise analysis.Theseproceedings are inspired by a conference held on the occasion of Prof. LudwigStreit¿s 75th birthday and celebrate his pioneering and ongoing work in thesefields.Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 312 pp. Englisch.

Buch. Zustand: Neu. Neuware -The infinite dimensional analysis as a branch of mathematical sciences was formed in the late 19th and early 20th centuries. Motivated by problems in mathematical physics, the first steps in this field were taken by V. Volterra, R. GateallX, P. Levy and M. Frechet, among others (see the preface to Levy[2]). Nevertheless, the most fruitful direction in this field is the infinite dimensional integration theory initiated by N. Wiener and A. N. Kolmogorov which is closely related to the developments of the theory of stochastic processes. It was Wiener who constructed for the first time in 1923 a probability measure on the space of all continuous functions (i. e. the Wiener measure) which provided an ideal math ematical model for Brownian motion. Then some important properties of Wiener integrals, especially the quasi-invariance of Gaussian measures, were discovered by R. Cameron and W. Martin[l, 2, 3]. In 1931, Kolmogorov[l] deduced a second partial differential equation for transition probabilities of Markov processes order with continuous trajectories (i. e. diffusion processes) and thus revealed the deep connection between theories of differential equations and stochastic processes. The stochastic analysis created by K. Ito (also independently by Gihman [1]) in the forties is essentially an infinitesimal analysis for trajectories of stochastic processes. By virtue of Ito's stochastic differential equations one can construct diffusion processes via direct probabilistic methods and treat them as function als of Brownian paths (i. e. the Wiener functionals).Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 312 pp. Englisch.

Buch. Zustand: Neu. Neuware -This volumepresents a collection of papers covering applications from a wide range ofsystems with infinitely many degrees of freedom studied using techniques fromstochastic and infinite dimensional analysis, e.g. Feynman path integrals, thestatistical mechanics of polymer chains, complex networks, and quantum fieldtheory. Systems of infinitely many degrees of freedom create their particularmathematical challenges which have been addressed by different mathematicaltheories, namely in the theories of stochastic processes, Malliavin calculusand especially white noise analysis.Theseproceedings are inspired by a conference held on the occasion of Prof. LudwigStreit¿s 75th birthday and celebrate his pioneering and ongoing work in thesefields.Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 312 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volumepresents a collection of papers covering applications from a wide range ofsystems with infinitely many degrees of freedom studied using techniques fromstochastic and infinite dimensional analysis, e.g. Feynman path integrals, thestatistical mechanics of polymer chains, complex networks, and quantum fieldtheory. Systems of infinitely many degrees of freedom create their particularmathematical challenges which have been addressed by different mathematicaltheories, namely in the theories of stochastic processes, Malliavin calculus,and especially white noise analysis.Theseproceedings are inspired by a conference held on the occasion of Prof. LudwigStreit's 75th birthday and celebrate his pioneering and ongoing work in thesefields.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volumepresents a collection of papers covering applications from a wide range ofsystems with infinitely many degrees of freedom studied using techniques fromstochastic and infinite dimensional analysis, e.g. Feynman path integrals, thestatistical mechanics of polymer chains, complex networks, and quantum fieldtheory. Systems of infinitely many degrees of freedom create their particularmathematical challenges which have been addressed by different mathematicaltheories, namely in the theories of stochastic processes, Malliavin calculus,and especially white noise analysis.Theseproceedings are inspired by a conference held on the occasion of Prof. LudwigStreit's 75th birthday and celebrate his pioneering and ongoing work in thesefields.

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Zustand: as new. Amsterdam : Royal Netherlands Academy of Arts and Sciences, 2000. Paperback. vi,282 pp. (Koninklijke Nederlandse Akademie van Wetenschappen ; Verhandelingen, Afd. Natuurkunde. Eerste reeks, 52). Condition : as new copy. ISBN 9789069842967. Keywords : MATHEMATICS,

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The infinite dimensional analysis as a branch of mathematical sciences was formed in the late 19th and early 20th centuries. Motivated by problems in mathematical physics, the first steps in this field were taken by V. Volterra, R. GateallX, P. Levy and M. Frechet, among others (see the preface to Levy[2]). Nevertheless, the most fruitful direction in this field is the infinite dimensional integration theory initiated by N. Wiener and A. N. Kolmogorov which is closely related to the developments of the theory of stochastic processes. It was Wiener who constructed for the first time in 1923 a probability measure on the space of all continuous functions (i. e. the Wiener measure) which provided an ideal math ematical model for Brownian motion. Then some important properties of Wiener integrals, especially the quasi-invariance of Gaussian measures, were discovered by R. Cameron and W. Martin[l, 2, 3]. In 1931, Kolmogorov[l] deduced a second partial differential equation for transition probabilities of Markov processes order with continuous trajectories (i. e. diffusion processes) and thus revealed the deep connection between theories of differential equations and stochastic processes. The stochastic analysis created by K. Ito (also independently by Gihman [1]) in the forties is essentially an infinitesimal analysis for trajectories of stochastic processes. By virtue of Ito's stochastic differential equations one can construct diffusion processes via direct probabilistic methods and treat them as function als of Brownian paths (i. e. the Wiener functionals).

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The infinite dimensional analysis as a branch of mathematical sciences was formed in the late 19th and early 20th centuries. Motivated by problems in mathematical physics, the first steps in this field were taken by V. Volterra, R. GateallX, P. Levy and M. Frechet, among others (see the preface to Levy[2]). Nevertheless, the most fruitful direction in this field is the infinite dimensional integration theory initiated by N. Wiener and A. N. Kolmogorov which is closely related to the developments of the theory of stochastic processes. It was Wiener who constructed for the first time in 1923 a probability measure on the space of all continuous functions (i. e. the Wiener measure) which provided an ideal math ematical model for Brownian motion. Then some important properties of Wiener integrals, especially the quasi-invariance of Gaussian measures, were discovered by R. Cameron and W. Martin[l, 2, 3]. In 1931, Kolmogorov[l] deduced a second partial differential equation for transition probabilities of Markov processes order with continuous trajectories (i. e. diffusion processes) and thus revealed the deep connection between theories of differential equations and stochastic processes. The stochastic analysis created by K. Ito (also independently by Gihman [1]) in the forties is essentially an infinitesimal analysis for trajectories of stochastic processes. By virtue of Ito's stochastic differential equations one can construct diffusion processes via direct probabilistic methods and treat them as function als of Brownian paths (i. e. the Wiener functionals).

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