Authors:
Applies martingale theory to the theory of Markov processes
Presents proofs and techniques in an easily adaptable style
Introductory summaries of standard probability theory and measure theory review basic knowledge before launching more sophisticated concepts
Recommended for graduate students, research workers and readers interested in Markov processes from a theoretical point of view
Includes supplementary material: sn.pub/extras
Part of the book series: Classics in Mathematics (CLASSICS)
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Table of contents (13 chapters)
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Front Matter
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Back Matter
About this book
Keywords
- Diffision processes
- MSC (2000): 60J60, 28A65
- Markov processes
- YellowSale2006
- differential equation
- diffusion
- diffusion process
- Excel
- Markov process
- Martingal
- Martingale
- measure
- measure theory
- partial differential equation
- probability
- probability theory
- statistics
- stochastic calculus
- stochastic differential equation
Authors and Affiliations
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Department of Mathematics, Massachusetts Institute of Technology, Cambridge, USA
Daniel W. Stroock
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Courant Institute of Mathematical Sciences, New York University, New York, USA
S. R. Srinivasa Varadhan
Bibliographic Information
Book Title: Multidimensional Diffusion Processes
Authors: Daniel W. Stroock, S. R. Srinivasa Varadhan
Series Title: Classics in Mathematics
DOI: https://doi.org/10.1007/3-540-28999-2
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2006
Softcover ISBN: 978-3-662-22201-0Published: 23 August 2014
eBook ISBN: 978-3-540-28999-9Published: 03 February 2007
Series ISSN: 1431-0821
Series E-ISSN: 2512-5257
Edition Number: 1
Number of Pages: XII, 338
Additional Information: Reprint of the 1997 Edition (Grundlehren der mathematischen Wissenschaften, Vol. 233)
Topics: Probability Theory and Stochastic Processes, Theoretical, Mathematical and Computational Physics