FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
|
|
- Title Advanced Stochastic Processes
- Author(s) Jan A. Van Casteren
- Publisher: BookBoon, University of Waterloo (2013)
- Hardcover/Paperback N/A
- eBook PDF (400+ pages)
- Language: English
- ISBN-10/ASIN: N/A
- ISBN-13: 978-8740303988
- Share This:
This comprehensive guide to Stochastic Processes gives a complete overview of the theory and addresses the most important applications. Pitched at a level accessible to beginning graduate students and researchers from applied disciplines, it is both a course book and a rich resource for individual readers.
In this book, which is basically self-contained, the following topics are treated thoroughly: Brownian motion as a Gaussian process, Brownian motion as a Markov process, and Brownian motion as a martingale. Brownian motion can also be considered as a functional limit of symmetric random walks, which is, to some extent, also discussed.
Related topics which are treated include Markov chains, renewal theory, the martingale problem, Ito calculus, cylindrical measures, and ergodic theory. Convergence of measures, stochastic differential equations, Feynman-Kac semigroups, and the Doob-Meyer decomposition theorem theorem are discussed in the second part of the book.
About the Authors- N/A
- Probability, Stochastic Process, Queueing Theory, etc.
- Statistics, and SAS Programming
- Geometry and Topology
- Combinatorics and Game Theory
- Advanced Stochastic Processes, Part I (Jan A. Van Casteren)
- Advanced Stochastic Processes, Part II (Jan A. Van Casteren)
- The Mirror Site (1) - Part I - PDF
-
Lectures on Stochastic Processes (Kiyosi Itô)
Well-written and accessible, this classic introduction to Stochastic Processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory.
-
Stochastic Differential Equations: Models and Numerics
The goal of this book is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and mathematical finance. Typically, these problems require numerical methods to obtain a solution.
-
Advanced Stochastic Processes (David Gamarnik)
This guide to Stochastic Processes covers a wide range of topics. Short, readable chapters aim for clarity rather than full generality. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling
-
Stochastic Calculus and Finance (Steven E. Shreve)
The book gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided.
-
Applied Stochastic Processes in Science and Engineering
This book introduces modern concepts of applied stochastic processes is written for a broad range of applications in diverse areas of engineering and the sciences. Written for a senior undergraduate course offered to students with a suitably mathematical background.
-
Stochastic Modeling and Control (Ivan Ganchev Ivanov)
The book provides a self-contained treatment on practical aspects of stochastic modeling and calculus including applications drawn from engineering, statistics, and computer science.
-
Stochastic Processes for Finance (Patrick Roger)
It describes the most important stochastic processes used in finance in a pedagogical way, especially Markov chains, Brownian motion and martingales. It also shows how mathematical tools like filtrations, Ito's lemma or Girsanov theorem should be understood in the framework of financial models.
:
|
|