应用预测最小二乘准则的AR模型判阶方法
STUDY OF AR MODEL ORDER SELECTION APPLYING CRITERION OF PREDICTIVE LEAST SQUARES
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摘要: 本文通过多种AR模型的判阶准则的比较提出了应用最小二乘预测误差的滑窗预测最小二乘(Sliding Window Predictive Least Squares, SWPLS)判阶准则.采用这种准则的主要优点除了准确的判阶性能外,对于时变AR模型具有良好的跟踪特性,同时算法容易实现在线实时处理.文中主要对时变模型参数和时变模型阶数的多种情况进行了判阶模拟,验证了文中提出的滑窗最小二乘预测判阶准则的有效性.
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关键词:
- 模型判阶; 滑窗数据; 格形结构
Abstract: A criterion called Sliding Window Predictive Least-Squares (SWPLS) order selection criterion is presented in this paper by comparison of several typical criteria of AR model order selection. In addition to property of fine order selection the criterion has advantage of good tracking property and can be easily implemented on-line in real time. The effectiveness of SWPLS criterion is verified by simulation experiment of order selection for models of time-varying parameter and time-varying order. -
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