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Smoothness Priors Analysis of Time Series
Kitagawa, G. (The Institute Of Statistical Mathematics, Tokyo, Japan); Gersch, W. (University Of Hawaii, Honolulu, Usa)
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Description for Smoothness Priors Analysis of Time Series
Paperback. The problems of modelling stationary and nonstationery time series from a Bayesian stochastic regression "smoothness priors" state space point of view are addressed in this work. Series: Lecture Notes in Statistics. Num Pages: 290 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 235 x 155 x 14. Weight in Grams: 880.
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. ... Read more
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. ... Read more
Product Details
Format
Paperback
Publication date
1996
Publisher
Springer-Verlag New York Inc. United States
Number of pages
290
Condition
New
Series
Lecture Notes in Statistics
Number of Pages
280
Place of Publication
New York, NY, United States
ISBN
9780387948195
SKU
V9780387948195
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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