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Continuous parameter markov processe...

Bhattacharya, R. N.

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Continuous parameter markov processes and stochastic differential equations

Record Type:	Electronic resources : Monograph/item
Title/Author:	Continuous parameter markov processes and stochastic differential equations/ by Rabi Bhattacharya, Edward C. Waymire.
Author:	Bhattacharya, R. N.
other author:	Waymire, Edward C.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xv, 506 p. :illustrations, digital ;24 cm.
[NT 15003449]:	1. A review of Martingaels, stopping times and the Markov property -- 2. Semigroup theory and Markov processes.-3. Regularity of Markov process sample paths -- 4. Continuous parameter jump Markov processes -- 5. Processes with independent increments -- 6. The stochastic integral -- 7. Construction of difficusions as solutions of stochastic differential equations -- 8. Itô's Lemma -- 9. Cameron-Martin-Girsanov theorem -- 10. Support of nonsingular diffusions -- 11. Transience and recurrence of multidimensional diffusions -- 12. Criteria for explosion -- 13. Absorption, reflection and other transformations of Markov processes -- 14. The speed of convergence to equilibrium of discrete parameter Markov processes and Diffusions -- 15. Probabilistic representation of solutions to certain PDEs -- 16. Probabilistic solution of the classical Dirichlet problem -- 17. The functional Central Limit Theorem for ergodic Markov processes -- 18. Asymptotic stability for singular diffusions -- 19. Stochastic integrals with L2-Martingales -- 20. Local time for Brownian motion -- 21. Construction of one dimensional diffusions by Semigroups -- 22. Eigenfunction expansions of transition probabilities for one-dimensional diffusions -- 23. Special Topic: The Martingale Problem -- 24. Special topic: multiphase homogenization for transport in periodic media -- 25. Special topic: skew random walk and skew Brownian motion -- 26. Special topic: piecewise deterministic Markov processes in population biology -- A. The Hille-Yosida theorem and closed graph theorem -- References -- Related textbooks and monographs.
Contained By:	Springer Nature eBook
Subject:	Markov processes. -
Online resource:	https://doi.org/10.1007/978-3-031-33296-8
ISBN:	9783031332968

Continuous parameter markov processes and stochastic differential equations
Bhattacharya, R. N.

Continuous parameter markov processes and stochastic differential equations[electronic resource] /by Rabi Bhattacharya, Edward C. Waymire. - Cham :Springer International Publishing :2023. - xv, 506 p. :illustrations, digital ;24 cm. - Graduate texts in mathematics,2992197-5612 ;. - Graduate texts in mathematics ;299..

1. A review of Martingaels, stopping times and the Markov property -- 2. Semigroup theory and Markov processes.-3. Regularity of Markov process sample paths -- 4. Continuous parameter jump Markov processes -- 5. Processes with independent increments -- 6. The stochastic integral -- 7. Construction of difficusions as solutions of stochastic differential equations -- 8. Itô's Lemma -- 9. Cameron-Martin-Girsanov theorem -- 10. Support of nonsingular diffusions -- 11. Transience and recurrence of multidimensional diffusions -- 12. Criteria for explosion -- 13. Absorption, reflection and other transformations of Markov processes -- 14. The speed of convergence to equilibrium of discrete parameter Markov processes and Diffusions -- 15. Probabilistic representation of solutions to certain PDEs -- 16. Probabilistic solution of the classical Dirichlet problem -- 17. The functional Central Limit Theorem for ergodic Markov processes -- 18. Asymptotic stability for singular diffusions -- 19. Stochastic integrals with L2-Martingales -- 20. Local time for Brownian motion -- 21. Construction of one dimensional diffusions by Semigroups -- 22. Eigenfunction expansions of transition probabilities for one-dimensional diffusions -- 23. Special Topic: The Martingale Problem -- 24. Special topic: multiphase homogenization for transport in periodic media -- 25. Special topic: skew random walk and skew Brownian motion -- 26. Special topic: piecewise deterministic Markov processes in population biology -- A. The Hille-Yosida theorem and closed graph theorem -- References -- Related textbooks and monographs.

This graduate text presents the elegant and profound theory of continuous parameter Markov processes and many of its applications. The authors focus on developing context and intuition before formalizing the theory of each topic, illustrated with examples. After a review of some background material, the reader is introduced to semigroup theory, including the Hille-Yosida Theorem, used to construct continuous parameter Markov processes. Illustrated with examples, it is a cornerstone of Feller's seminal theory of the most general one-dimensional diffusions studied in a later chapter. This is followed by two chapters with probabilistic constructions of jump Markov processes, and processes with independent increments, or Lévy processes. The greater part of the book is devoted to Itô's fascinating theory of stochastic differential equations, and to the study of asymptotic properties of diffusions in all dimensions, such as explosion, transience, recurrence, existence of steady states, and the speed of convergence to equilibrium. A broadly applicable functional central limit theorem for ergodic Markov processes is presented with important examples. Intimate connections between diffusions and linear second order elliptic and parabolic partial differential equations are laid out in two chapters, and are used for computational purposes. Among Special Topics chapters, two study anomalous diffusions: one on skew Brownian motion, and the other on an intriguing multi-phase homogenization of solute transport in porous media.

ISBN: 9783031332968

Standard No.: 10.1007/978-3-031-33296-8doiSubjects--Topical Terms:

532104
Markov processes.

LC Class. No.: QA274.7 / .B43 2023

Dewey Class. No.: 519.233

Continuous parameter markov processes and stochastic differential equations
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505 0 $a 1. A review of Martingaels, stopping times and the Markov property -- 2. Semigroup theory and Markov processes.-3. Regularity of Markov process sample paths -- 4. Continuous parameter jump Markov processes -- 5. Processes with independent increments -- 6. The stochastic integral -- 7. Construction of difficusions as solutions of stochastic differential equations -- 8. Itô's Lemma -- 9. Cameron-Martin-Girsanov theorem -- 10. Support of nonsingular diffusions -- 11. Transience and recurrence of multidimensional diffusions -- 12. Criteria for explosion -- 13. Absorption, reflection and other transformations of Markov processes -- 14. The speed of convergence to equilibrium of discrete parameter Markov processes and Diffusions -- 15. Probabilistic representation of solutions to certain PDEs -- 16. Probabilistic solution of the classical Dirichlet problem -- 17. The functional Central Limit Theorem for ergodic Markov processes -- 18. Asymptotic stability for singular diffusions -- 19. Stochastic integrals with L2-Martingales -- 20. Local time for Brownian motion -- 21. Construction of one dimensional diffusions by Semigroups -- 22. Eigenfunction expansions of transition probabilities for one-dimensional diffusions -- 23. Special Topic: The Martingale Problem -- 24. Special topic: multiphase homogenization for transport in periodic media -- 25. Special topic: skew random walk and skew Brownian motion -- 26. Special topic: piecewise deterministic Markov processes in population biology -- A. The Hille-Yosida theorem and closed graph theorem -- References -- Related textbooks and monographs.
520 $a This graduate text presents the elegant and profound theory of continuous parameter Markov processes and many of its applications. The authors focus on developing context and intuition before formalizing the theory of each topic, illustrated with examples. After a review of some background material, the reader is introduced to semigroup theory, including the Hille-Yosida Theorem, used to construct continuous parameter Markov processes. Illustrated with examples, it is a cornerstone of Feller's seminal theory of the most general one-dimensional diffusions studied in a later chapter. This is followed by two chapters with probabilistic constructions of jump Markov processes, and processes with independent increments, or Lévy processes. The greater part of the book is devoted to Itô's fascinating theory of stochastic differential equations, and to the study of asymptotic properties of diffusions in all dimensions, such as explosion, transience, recurrence, existence of steady states, and the speed of convergence to equilibrium. A broadly applicable functional central limit theorem for ergodic Markov processes is presented with important examples. Intimate connections between diffusions and linear second order elliptic and parabolic partial differential equations are laid out in two chapters, and are used for computational purposes. Among Special Topics chapters, two study anomalous diffusions: one on skew Brownian motion, and the other on an intriguing multi-phase homogenization of solute transport in porous media.
650 0 $a Markov processes. $3 532104
650 0 $a Stochastic processes. $3 520663
650 0 $a Differential equations. $3 517952
650 1 4 $a Probability Theory. $3 3538789
650 2 4 $a Applications of Mathematics. $3 890893
700 1 $a Waymire, Edward C. $3 692131
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Graduate texts in mathematics ; $v 299. $3 3669247
856 4 0 $u https://doi.org/10.1007/978-3-031-33296-8
950 $a Mathematics and Statistics (SpringerNature-11649)