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Books > Science & Mathematics > Mathematics > Probability & statistics
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Measure Theory and Filtering - Introduction and Applications (Hardcover)
Loot Price: R2,665
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Measure Theory and Filtering - Introduction and Applications (Hardcover)
Series: Cambridge Series in Statistical and Probabilistic Mathematics
Expected to ship within 10 - 15 working days
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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.
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