Genshiro Kitagawa

(Author)

Smoothness Priors Analysis of Time Series (1996)Paperback - 1996, 9 August 1996

Smoothness Priors Analysis of Time Series (1996)
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Part of Series
Lecture Notes in Statistics
Part of Series
Ima Volumes in Mathematics and Its Applications
Print Length
280 pages
Language
English
Publisher
Springer
Date Published
9 Aug 1996
ISBN-10
0387948198
ISBN-13
9780387948195

Description

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.

Product Details

Authors:
Genshiro KitagawaWill Gersch
Book Edition:
1996
Book Format:
Paperback
Country of Origin:
US
Date Published:
9 August 1996
Dimensions:
23.39 x 15.6 x 1.5 cm
ISBN-10:
0387948198
ISBN-13:
9780387948195
Language:
English
Location:
New York, NY
Pages:
280
Publisher:
Weight:
394.63 gm

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