| 引用本文: | 王红军, 田铮, 党怀义.非线性时间序列建模的异方差混合双AR模型[J].控制理论与应用,2006,23(6):879~885.[点击复制] |
| WANG Hong-jun, TIAN Zheng , DANG Huai-yi.Heteroscedastic mixture double-autoregressive model for modeling nonlinear time series[J].Control Theory and Technology,2006,23(6):879~885.[点击复制] |
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| 非线性时间序列建模的异方差混合双AR模型 |
| Heteroscedastic mixture double-autoregressive model for modeling nonlinear time series |
| 摘要点击 1822 全文点击 1524 投稿时间：2005-07-28 修订日期：2005-12-08 |
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| DOI编号 |
| 2006,23(6):879-885 |
| 中文关键词 异方差混合双自回归模型 平稳性 BIC准则 ECM算法 非对称分布 多峰分布 条件异方差 |
| 英文关键词 heteroscedastic mixture double-autoregressive model stationarity Bayes information criterion expectation conditional maximization (ECM)algorithm asymmetric distribution multimodal distribution conditional heteroscedasticity |
| 基金项目 国家自然科学基金资助项目(60375003); 国家航空基金资助项目(03153059). |
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| 中文摘要 |
| 研究了可用于非线性时间序列建模的异方差混合双自回归模型(heteroscedastic mixture doubleautoregressive model, HMDAR), 给出了HMDAR模型的平稳性条件, 利用ECM (expectation conditional maximization) 算法来估计模型的参数, 运用BIC(Bayes information criterion) 准则来选择模型. HMDAR模型条件分布富于变化的特征使它能够对具有非对称或多峰分布的序列进行建模, 将HMDAR模型应用于几个模拟和实际数据集均得到了较为满意的结果, 特别是对波动较大的序列, HMDAR模型能比其他模型更好地捕捉到数据序列的特征. |
| 英文摘要 |
| The heteroscedastic mixture double-autoregressive (HMDAR) model, which is designed to model nonlinear time series, is investigated in this paper. Firstly, the stationary conditions are derived. Secondly, the parameters are estimated via expectation conditional maximization (ECM) algorithm. Thirdly, the Bayes information criterion (BIC) is used to select the model. The varied feature of conditional distributions makes the HMDAR model capable of modeling time series with asymmetric or multimodal distribution. Finally, the model was applied to several simulated and real data sets with satisfactory results. Especially to a highly time-variant series, the HMDAR model shows better performance than other competing models in data capturing． |
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