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