Probability and Stochastic Processes
Ionut Florescu
Sold by Kennys Bookstore, Olney, MD, U.S.A.
AbeBooks Seller since October 9, 2009
New - Hardcover
Condition: New
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Add to basketSold by Kennys Bookstore, Olney, MD, U.S.A.
AbeBooks Seller since October 9, 2009
Condition: New
Quantity: 1 available
Add to basketA comprehensive and accessible presentation of probability and stochastic processes with emphasis on key theoretical concepts and real-world applications With a sophisticated approach, Probability and Stochastic Processes successfully balances theory and applications in a pedagogical and accessible format. Num Pages: 576 pages, , black & white tables, figures. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 166 x 243 x 35. Weight in Grams: 908. . 2014. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
Seller Inventory # V9780470624555
A comprehensive and accessible presentation of probability and stochastic processes with emphasis on key theoretical concepts and real-world applications
With a sophisticated approach, Probability and Stochastic Processes successfully balances theory and applications in a pedagogical and accessible format. The book’s primary focus is on key theoretical notions in probability to provide a foundation for understanding concepts and examples related to stochastic processes.
Organized into two main sections, the book begins by developing probability theory with topical coverage on probability measure; random variables; integration theory; product spaces, conditional distribution, and conditional expectations; and limit theorems. The second part explores stochastic processes and related concepts including the Poisson process, renewal processes, Markov chains, semi-Markov processes, martingales, and Brownian motion. Featuring a logical combination of traditional and complex theories as well as practices, Probability and Stochastic Processes also includes:
Ionut Florescu, PhD, is Research Associate Professor of Financial Engineering and Director of the Hanlon Financial Systems Lab at Stevens Institute of Technology. His areas of research interest include stochastic volatility, stochastic partial differential equations, Monte Carlo methods, and numerical methods for stochastic processes. He is also the coauthor of Handbook of Probability and coeditor of Handbook of Modeling High-Frequency Data in Finance, both published by Wiley.
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