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題名 | A Unified Approach to Estimating and Modeling Linear and Nonlinear Time Series |
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作者姓名(外文) | Chen,Cathy W. S.; McCulloch,Robert E.; Tsay,Ruey S.; | 書刊名 | Statistica Sinica |
卷期 | 7:2 1997.04[民86.04] |
頁次 | 頁451-472 |
分類號 | 319.711 |
關鍵詞 | 雙線性模式; 模式選取; 時間序列; Bayesian model selection; Bilinear model; Gibbs sampler; Mixed model; Stochastic volatility; Threshold autoregressive model; |
語文 | 英文(English) |
英文摘要 | In this article, we propose a unified approach to estimating and modeling univariate time series. The approach applies to both linear and nonlinear time series models and can be used to discriminate non-nested nonlinear models. For example, it can discriminate between threshold autoregressive and bilinear models or between autoregressive and moving average models. It can also be used to estimate and discriminate between symmetric conditional heteroscedastic models commonly used in volatility studies of financial time series. The proposed approach is based on Gibbs sampling and may required substantial amounts of computing in some applications. We illustrate the proposed approach by some simulated and real examples. Comparison with other existing methods is also discussed. |
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