Time series decomposition

被引:81
作者
West, M
机构
[1] Institute of Statistics and Decision Sciences, Duke University, Durham
基金
美国国家科学基金会;
关键词
autoregressive process; Bayesian computation; dynamic linear model; quasi-periodic component; state space model; time-varying cycle;
D O I
10.1093/biomet/84.2.489
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
A constructive result on time series decomposition is presented and illustrated. Developed through dynamic linear models, the decomposition is useful in analysis of an observed time series through inference about underlying, latent component series that may have physical interpretations. Particular special cases include slate space autoregressive component models, in which the decomposition is useful for isolating latent, quasi-cyclical components, in particular. Brief summaries of analyses of some geological records related to climatic change illustrate the result.
引用
收藏
页码:489 / 494
页数:6
相关论文
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WEST M, 1997, BAYESIAN ROBUSTNESS, V2
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West M., 2006, Bayesian forecasting and dynamic models
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WEST M, 1996, MAXIMUM ENTROPY BAYE, V15, P23
[15]  
WEST M, 1996, BAYESIAN STAT, V5, P461