A local vector autoregressive framework and its applications to multivariate time series monitoring and forecasting
A local vector autoregressive framework and its applications to multivariate time series monitoring and forecasting
复制标题
局部向量自回归框架及其在多元时间序列监测和预测中的应用
DOI：
10.4310/sii.2013.v6.n4.a8
复制
发表时间：
2013
影响因子：
0.8
通讯作者：
Linlin Niu
中科院分区：
文献类型：
--
作者：
Ying Chen;Bo Li;Linlin Niu
我们提出的局部向量自回归（LVAR）模型具有时变参数，使其能够安全地用于平稳和非平稳情况。估计是在局部均匀性的区间上进行的，其中参数近似恒定。局部区间是在序贯检验过程中确定的。通过数值分析和真实的数据应用，验证了该模型的监测功能和预报性能。
Our proposed local vector autoregressive (LVAR) model has time-varying parameters that allow it to be safely used in both stationary and non-stationary situations. The estimation is conducted over an interval of local homogeneity where the parameters are approximately constant. The local interval is identified in a sequential testing procedure. Numerical analysis and real data application are conducted to illustrate the monitoring function and forecast performance of the proposed model.