Florescu | Probability and Stochastic Processes | E-Book | sack.de
E-Book

E-Book, Englisch, 576 Seiten, E-Book

Florescu Probability and Stochastic Processes

E-Book, Englisch, 576 Seiten, E-Book

ISBN: 978-1-118-59320-2
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)



A comprehensive and accessible presentation of probabilityand stochastic processes with emphasis on key theoretical conceptsand real-world applications
With a sophisticated approach, Probability and StochasticProcesses successfully balances theory and applications in apedagogical and accessible format. The book's primary focusis on key theoretical notions in probability to provide afoundation for understanding concepts and examples related tostochastic processes.
Organized into two main sections, the book begins by developingprobability theory with topical coverage on probability measure;random variables; integration theory; product spaces, conditionaldistribution, and conditional expectations; and limit theorems. Thesecond part explores stochastic processes and related conceptsincluding the Poisson process, renewal processes, Markov chains,semi-Markov processes, martingales, and Brownian motion. Featuringa logical combination of traditional and complex theories as wellas practices, Probability and Stochastic Processes alsoincludes:
* Multiple examples from disciplines such as business,mathematical finance, and engineering
* Chapter-by-chapter exercises and examples to allow readers totest their comprehension of the presented material
* A rigorous treatment of all probability and stochasticprocesses concepts
An appropriate textbook for probability and stochastic processescourses at the upper-undergraduate and graduate level inmathematics, business, and electrical engineering, Probabilityand Stochastic Processes is also an ideal reference forresearchers and practitioners in the fields of mathematics,engineering, and finance.
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Autoren/Hrsg.


Weitere Infos & Material


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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