| 引用本文: | 王红军, 田铮.非线性时间序列建模的混合自回归滑动平均模型[J].控制理论与应用,2005,22(6):875~881.[点击复制] |
| WANG Hong-jun,TIAN Zheng.Mixed autoregressive moving average model for modeling nonlinear time series[J].Control Theory and Technology,2005,22(6):875~881.[点击复制] |
|
| 非线性时间序列建模的混合自回归滑动平均模型 |
| Mixed autoregressive moving average model for modeling nonlinear time series |
| 摘要点击 2092 全文点击 2191 投稿时间：2004-07-30 修订日期：2005-01-31 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 |
| 2005,22(6):875-881 |
| 中文关键词 混合自回归滑动平均模型 自相关 平稳性 期望极大化算法 条件异方差 |
| 英文关键词 mixed autoregressive moving average(MARMA) model autocorrelation stationarity EM(expectation maximization) algorithm 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(03I53059). |
|
| 中文摘要 |
| 提出了一类用于非线性时间序列建模的混合自回归滑动平均模型(MARMA).该模型是由K个平稳或非平稳的ARMA分量经过混合得到的.讨论了MARMA模型的平稳性条件和自相关函数.给出了MARMA模型参数估计的期望极大化(expectation maximization)算法.运用贝叶斯信息准则(Bayes information criterion)来选择该模型.MARMA模型分布形式富于变化的特征使得它能够对具有多峰分布以及条件异方差的序列进行建模.通过两个实例验证了该模型,并和其他模型进行比较,结果表明MARMA模型能够更好地描述这些数据的特征. |
| 英文摘要 |
| A mixed autoregressive moving average(MARMA) model is proposed for modeling nonlinear time series.The model consists of K stationary or nonstationary ARMA components.The stationary conditions and autocorrelation function of the MARMA process are investigated.The estimation of parameters is easily performed via expectation maximization(EM) algorithm.The Bayes information criterion(BIC) is used as a tool for the MARMA model selection.The varried feature of conditional distributions of the MARMA model makes it capable of modeling time series with multimodal conditional distributions and with hetero scedasticity.The model is applied to two real data sets and compared with other competing models.The MARMA model appears to capture features of the data better than other competing models do. |