Stochastic Flows and Jump-Diffusions: Probability Theory and Stochastic Modelling, cartea 92
Autor Hiroshi Kunitaen Limba Engleză Hardback – 9 apr 2019
This monograph presents a modern treatment of (1) stochastic differential equations and (2) diffusion and jump-diffusion processes. The simultaneous treatment of diffusion processes and jump processes in this book is unique: Each chapter starts from continuous processes and then proceeds to processes with jumps.
In the first part of the book, it is shown that solutions of stochastic differential equations define stochastic flows of diffeomorphisms. Then, the relation between stochastic flows and heat equations is discussed. The latter part investigates fundamental solutions of these heat equations (heat kernels) through the study of the Malliavin calculus. The author obtains smooth densities for transition functions of various types of diffusions and jump-diffusions and shows that these density functions are fundamental solutions for various types of heat equations and backward heat equations. Thus, in this book fundamental solutions for heat equations and backward heatequations are constructed independently of the theory of partial differential equations.
Researchers and graduate student in probability theory will find this book very useful.
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Specificații
ISBN-13: 9789811338007
ISBN-10: 9811338000
Pagini: 280
Ilustrații: XVII, 352 p. 145 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.72 kg
Ediția:1st ed. 2019
Editura: Springer Nature Singapore
Colecția Springer
Seria Probability Theory and Stochastic Modelling
Locul publicării:Singapore, Singapore
ISBN-10: 9811338000
Pagini: 280
Ilustrații: XVII, 352 p. 145 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.72 kg
Ediția:1st ed. 2019
Editura: Springer Nature Singapore
Colecția Springer
Seria Probability Theory and Stochastic Modelling
Locul publicării:Singapore, Singapore
Cuprins
Preface.- Introduction.- 1.Probability distributions and stochastic processes.- 2.Stochastic integrals based on Wiener processes and Poisson random measures.- 3.Stochastic differential equations and stochastic flows.- 4.Diffusions, jump-diffusions and heat equations.- 5.Malliavin calculus for Wiener processes and Poisson random measures.- 6.Smooth densities and heat kernels.- 7.Jump-diffusions on manifolds and smooth densities.- Bibliography.- Index.
Recenzii
“The presentation is self-contained, clear and precise. The book is definitely a must-read for researchers in the field of stochastic flows and stochastic differential equations.” (G. V. Riabov, Mathematical Reviews, October, 2020)
Notă biografică
Kunita was an invited speaker at the ICM 1986.
Textul de pe ultima copertă
This monograph presents a modern treatment of (1) stochastic differential equations and (2) diffusion and jump-diffusion processes. The simultaneous treatment of diffusion processes and jump processes in this book is unique: Each chapter starts from continuous processes and then proceeds to processes with jumps.
In the first part of the book, it is shown that solutions of stochastic differential equations define stochastic flows of diffeomorphisms. Then, the relation between stochastic flows and heat equations is discussed. The latter part investigates fundamental solutions of these heat equations (heat kernels) through the study of the Malliavin calculus. The author obtains smooth densities for transition functions of various types of diffusions and jump-diffusions and shows that these density functions are fundamental solutions for various types of heat equations and backward heat equations. Thus, in this book fundamental solutions for heat equations and backward heatequations are constructed independently of the theory of partial differential equations.
Researchers and graduate student in probability theory will find this book very useful.
Caracteristici
Provides systematic treatment of the Malliavin calculus on the Wiener–Poisson space, introducing Sobolev norms Uses the flow property of the solution of stochastic differential equations and application to dual jump-diffusions Is a study of fundamental solutions through stochastic analysis without the aid of partial differential equations