Measure Theory and Filtering

Name: Measure Theory and Filtering
SKU: 2012589
Price: 248.00 NZD
Availability: InStock

Introduction and Applications

By:

Format:

Hardback

Series:

Cambridge Series in Statistical and Probabilistic Mathematics

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Description

The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus based probability theory. As conditional expectation is the key concept, the correct setting for filtering theory is that of a probability space. Graduate engineers, mathematicians and those working in quantitative finance wishing to use filtering techniques will find in the first half of this book an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion. Exercises are included. The book then provides an excellent users' guide to filtering: basic theory is followed by a thorough treatment of Kalman filtering, including recent results which extend the Kalman filter to provide parameter estimates. These ideas are then applied to problems arising in finance, genetics and population modelling in three separate chapters, making this a comprehensive resource for both practitioners and researchers.

Author Biography:

Lakhdar Aggoun is an Associate Professor in the Department of Mathematics and Statistics at Sultan Qabos University, Oman. Robert Elliott is the RBC Financial Group Professor of Finance at the University of Calgary, Canada.

Release date NZ

September 13th, 2004

Author

Audience

Professional & Vocational

Pages

270

Series

Cambridge Series in Statistical and Probabilistic Mathematics

Dimensions

184x262x26

ISBN-13

9780521838030

Product ID

2012589

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