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Measure Theory and Filtering: Introduction with Applications (Cambridge Series in Statistical and Probabilistic Mathematics) - Hardcover
Synopsis
Aimed primarily at those outside of the field of statistics, this book not only provides an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion, but develops into an excellent user's guide to filtering. Including exercises for students, it will be a complete resource for engineers, signal processing researchers, or anyone with an interest in practical implementation of filtering techniques, in particular, the Kalman filter. Three separate chapters concentrate on applications arising in finance, genetics, and population modelling.
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About the Author
Robert Elliott is the RBC Financial Group Professor of Finance at the University of Calgary, Canada.
Review
"It is well written and self-contained. I am convinced that it will raise a lot of interest and remain a reference for a long time to come." Alain Bensoussan, University of Texas at Dallas
"About this title" may belong to another edition of this title.
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Measure Theory and Filtering: Introduction and Applications: 15 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 15)
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Cambridge University Press, 2004
ISBN 10: 0521838037
ISBN 13: 9780521838030
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Measure Theory and Filtering: Introduction and Applications: 15 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 15)
Published by
Cambridge University Press, 2004
ISBN 10: 0521838037
ISBN 13: 9780521838030
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Measure Theory and Filtering: Introduction and Applications. (Cambridge Series in Statistical and Probabilistic Mathematics)
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Condition: Very Good. *FREE DOMESTIC SHIPPING until Monday, June 30* 258 pp., hardcover, previous owner's inscription to front free endpaper else very good. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Seller Inventory # ZB1316613
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Measure Theory and Filtering: Introduction with Applications (Cambridge Series in Statistical and Probabilistic Mathematics)
Published by
Cambridge University Press, 2004
ISBN 10: 0521838037
ISBN 13: 9780521838030
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Measure Theory and Filtering: Introduction with Applications (Cambridge Series in Statistical and Probabilistic Mathematics)
Published by
Cambridge University Press, 2004
ISBN 10: 0521838037
ISBN 13: 9780521838030
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Measure Theory and Filtering: Introduction and Applications (Hardcover)
Published by
Cambridge University Press, Cambridge, 2004
ISBN 10: 0521838037
ISBN 13: 9780521838030
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Hardcover
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Hardcover. Condition: new. Hardcover. 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. Aimed primarily at those outside of the field of statistics, this book not only provides an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion, but develops into an excellent user's guide to filtering. Including exercises for students, it will be a complete resource for engineers, signal processing researchers, or anyone with an interest in practical implementation of filtering techniques, in particular, the Kalman filter. Three separate chapters concentrate on applications arising in finance, genetics, and population modelling. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521838030
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Measure Theory and Filtering: An Introduction With Applications
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Hardcover. Condition: Brand New. 337 pages. 10.25x7.25x1.00 inches. In Stock. This item is printed on demand. Seller Inventory # __0521838037
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Measure Theory and Filtering: Introduction with Applications (Cambridge Series in Statistical and Probabilistic Mathematics)
Published by
Cambridge University Press, 2004
ISBN 10: 0521838037
ISBN 13: 9780521838030
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Measure Theory and Filtering: Introduction and Applications
Published by
Cambridge University Press, 2004
ISBN 10: 0521838037
ISBN 13: 9780521838030
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Hardcover
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Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 694. Seller Inventory # C9780521838030
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Measure Theory and Filtering: Introduction and Applications (Hardcover)
Published by
Cambridge University Press, Cambridge, 2004
ISBN 10: 0521838037
ISBN 13: 9780521838030
New
Hardcover
Seller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. 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. Aimed primarily at those outside of the field of statistics, this book not only provides an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion, but develops into an excellent user's guide to filtering. Including exercises for students, it will be a complete resource for engineers, signal processing researchers, or anyone with an interest in practical implementation of filtering techniques, in particular, the Kalman filter. Three separate chapters concentrate on applications arising in finance, genetics, and population modelling. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780521838030
Quantity: 1 available