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Smoothness Priors Analysis of Time Series

by Genshiro Kitagawa
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Current price ₹9,548.00
Original price ₹14,689.00
Original price ₹14,689.00
Original price ₹14,689.00
(-35%)
₹9,548.00
Current price ₹9,548.00

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Book cover type: Paperback
  • ISBN13: 9780387948195
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 280
  • Original Price: EUR 129.99
  • Language: English
  • Edition: 1996
  • Item Weight: 421 grams
  • BISAC Subject(s): General, Probability & Statistics / General, and Mathematical Analysis

Smoothness Priors Analysis of Time Series addresses some of the problems of modeling stationary and nonstationary time series primarily from a Bayesian stochastic regression "smoothness priors" state space point of view. Prior distributions on model coefficients are parametrized by hyperparameters. Maximizing the likelihood of a small number of hyperparameters permits the robust modeling of a time series with relatively complex structure and a very large number of implicitly inferred parameters. The critical statistical ideas in smoothness priors are the likelihood of the Bayesian model and the use of likelihood as a measure of the goodness of fit of the model. The emphasis is on a general state space approach in which the recursive conditional distributions for prediction, filtering, and smoothing are realized using a variety of nonstandard methods including numerical integration, a Gaussian mixture distribution-two filter smoothing formula, and a Monte Carlo "particle-path tracing" method in which the distributions are approximated by many realizations. The methods are applicable for modeling time series with complex structures.

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