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Order Selection for General Expression of Nonlinear Autoregressive Model Based on Multivariate Stepwise Regression

机译:基于多变量逐步回归的非线性自回归模型一般表达的订单选择

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An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.
机译:提出了一种基于多个逐步回归的订单选择方法,用于非线性自回归模型的一般表达式,其将模型顺序问题转换为多元线性回归方程的变量选择。采用部分自相关函数来定义GNAR模型中的线性术语。结果设置为初始模型,然后逐渐引入非线性术语。选择统计数据来研究模型特征的新引入和最初存在的变量的改进,这些特征是通过确定模型变量保留或消除的模型变量。因此,通过数据拟合效果测量或显着测试获得最佳模型。仿真和经典时间序列数据实验结果表明,提出的方法简单,可靠,可应用于实用工程。

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