Measure Theory and Filtering: Introduction and Applications - Couverture rigide
Livre 9 sur 45: Cambridge Series in Statistical and Probabilistic Mathematics
Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Measure Theory and Filtering: Introduction with Applications (Cambridge Series in Statistical and Probabilistic Mathematics)
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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)
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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)
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ISBN 13 : 9780521838030
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Measure Theory and Filtering: Introduction with Applications (Cambridge Series in Statistical and Probabilistic Mathematics)
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ISBN 13 : 9780521838030
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Measure Theory and Filtering: Introduction and Applications (Hardcover)
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Cambridge University Press, Cambridge, 2004
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ISBN 13 : 9780521838030
Neuf
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Hardcover. Etat : 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. N° de réf. du vendeur 9780521838030
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Measure Theory and Filtering: Introduction with Applications (Cambridge Series in Statistical and Probabilistic Mathematics)
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Cambridge University Press, 2004
ISBN 10 : 0521838037
ISBN 13 : 9780521838030
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Couverture rigide
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Measure Theory and Filtering: An Introduction With Applications
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Cambridge Univ Pr, 2004
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ISBN 13 : 9780521838030
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Measure Theory and Filtering: Introduction and Applications
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Cambridge University Press, 2004
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ISBN 13 : 9780521838030
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Edition internationale
MEASURE THEORY AND FLITERING INTRODUCTION WITH APPLICATIONS (HB 2004)
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ISBN 13 : 9780521838030
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Measure Theory and Filtering: Introduction and Applications (Hardcover)
Edité par
Cambridge University Press, Cambridge, 2004
ISBN 10 : 0521838037
ISBN 13 : 9780521838030
Neuf
Couverture rigide
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Hardcover. Etat : 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. N° de réf. du vendeur 9780521838030
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