ISSN:
1572-9052
Keywords:
Time series
;
Bayesian approach
;
signal decomposition
;
linear filter
;
variable kernel
;
curve smoothing
;
smoothness prior
;
seasonal component model
;
quasi-sinusoidal wave extraction
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract Frequency domain properties of the operators to decompose a time series into the multi-components along the Akaike's Bayesian model (Akaike (1980, Bayesian Statistics, 143–165, University Press, Valencia, Spain)) are shown. In that analysis a normal disturbance-linear-stochastic regression prior model is applied to the time series. A prior distribution, characterized by a small number of hyperparameters, is specified for model parameters. The posterior distribution is a linear function (filter) of observations. Here we use frequency domain analysis or filter characteristics of several prior models parametrically as a function of the hyperparameters.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00053367
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