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Fixed Interval Smoothing for State Space Models (Paperback, Softcover reprint of the original 1st ed. 2001)
Loot Price: R2,741
Discovery Miles 27 410
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Fixed Interval Smoothing for State Space Models (Paperback, Softcover reprint of the original 1st ed. 2001)
Series: The Springer International Series in Engineering and Computer Science, 609
Expected to ship within 10 - 15 working days
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Total price: R2,761
Discovery Miles: 27 610
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Fixed-interval smoothing is a method of extracting useful
information from inaccurate data. It has been applied to problems
in engineering, the physical sciences, and the social sciences, in
areas such as control, communications, signal processing,
acoustics, geophysics, oceanography, statistics, econometrics, and
structural analysis. This monograph addresses problems for which a
linear stochastic state space model is available, in which case the
objective is to compute the linear least-squares estimate of the
state vector in a fixed interval, using observations previously
collected in that interval. The author uses a geometric approach
based on the method of complementary models. Using the simplest
possible notation, he presents straightforward derivations of the
four types of fixed-interval smoothing algorithms, and compares the
algorithms in terms of efficiency and applicability. Results show
that the best algorithm has received the least attention in the
literature.Fixed Interval Smoothing for State Space Models: *
includes new material on interpolation, fast square root
implementations, and boundary value models; * is the first book
devoted to smoothing; * contains an annotated bibliography of
smoothing literature; * uses simple notation and clear derivations;
* compares algorithms from a computational perspective; *
identifies a best algorithm. Fixed Interval Smoothing for State
Space Models will be the primary source for those wanting to
understand and apply fixed-interval smoothing: academics,
researchers, and graduate students in control, communications,
signal processing, statistics and econometrics.
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