Measure Theory and Filtering: Introduction and Applications - Brossura
Libro 9 di 45: Cambridge Series in Statistical and Probabilistic Mathematics
Sinossi
This book is a resource for non-statisticians implementing filtering methods, which covers applications in finance, genetics and population.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Recensione
Review of the hardback: '... useful to those students and scientists in signal processing, mathematical finance and genetics, wishing to incorporate measure-theoretic probability techniques into their predictions. It is also an excellent user's guide to filtering with interesting applications arising in difference arenas.' Journal of Applied Statistics
Descrizione del libro
This book provides an accessible introduction to measure theory and stochastic calculus, and develops into an excellent users' guide to filtering. A complete resource for engineers, or anyone with an interest in implementation of filtering techniques. Three chapters concentrate on applications from finance, genetics and population modelling. Also includes exercises.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Measure Theory and Filtering: Introduction and Applications (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 15)
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Measure Theory and Filtering: Introduction and Applications (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 15)
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Measure Theory and Filtering: Introduction and Applications
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Cambridge University Press, 2012
ISBN 10: 1107410711
ISBN 13: 9781107410718
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Paperback. Condizione: Brand New. 1st edition. 268 pages. 9.75x6.75x0.75 inches. In Stock. This item is printed on demand. Codice articolo __1107410711
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Measure Theory and Filtering (Paperback)
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Cambridge University Press, Cambridge, 2012
ISBN 10: 1107410711
ISBN 13: 9781107410718
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Paperback. Condizione: new. Paperback. 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. This book provides an accessible introduction to measure theory and stochastic calculus, and develops into an excellent users' guide to filtering. A complete resource for engineers, or anyone with an interest in implementation of filtering techniques. Three chapters concentrate on applications from finance, genetics and population modelling. Also includes exercises. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781107410718
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Measure Theory and Filtering
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Cambridge University Press CUP, 2012
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ISBN 13: 9781107410718
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Measure Theory and Filtering (Paperback)
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Cambridge University Press, Cambridge, 2012
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ISBN 13: 9781107410718
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Paperback. Condizione: new. Paperback. 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. This book provides an accessible introduction to measure theory and stochastic calculus, and develops into an excellent users' guide to filtering. A complete resource for engineers, or anyone with an interest in implementation of filtering techniques. Three chapters concentrate on applications from finance, genetics and population modelling. Also includes exercises. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781107410718
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Measure Theory and Filtering
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides an accessible introduction to measure theory and stochastic calculus, and develops into an excellent users guide to filtering. A complete resource for engineers, or anyone with an interest in implementation of filtering techniques. Thre. Codice articolo 447217884
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Measure Theory and Filtering (Paperback)
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Cambridge University Press, Cambridge, 2012
ISBN 10: 1107410711
ISBN 13: 9781107410718
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Paperback. Condizione: new. Paperback. 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. This book provides an accessible introduction to measure theory and stochastic calculus, and develops into an excellent users' guide to filtering. A complete resource for engineers, or anyone with an interest in implementation of filtering techniques. Three chapters concentrate on applications from finance, genetics and population modelling. Also includes exercises. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9781107410718
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