NONLINEAR ADDITIVE ARX MODELS
NONLINEAR ADDITIVE ARX MODELS
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DOI：
10.2307/2290787
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发表时间：
1993-09-01
影响因子：
3.7
通讯作者：
TSAY, RS
中科院分区：
文献类型：
--
作者：
CHEN, R;TSAY, RS
本文考虑了一类用于非线性时间序列分析的带外生变量的非线性可加自回归模型，并提出了两种建模方法。提出的程序使用两个backfitting技术（ACE和BRUTO算法）来识别所涉及的非线性函数，并使用最佳子集回归和回归分析中的变量选择的方法来确定最终的模型。最后用仿真和真实的算例进行了说明。
We consider in this article a class of nonlinear additive autoregressive models with exogenous variables for nonlinear time series analysis and propose two modeling procedures for building such models. The procedures proposed use two backfitting techniques (the ACE and BRUTO algorithms) to identify the nonlinear functions involved and use the methods of best subset regression and variable selection in regression analysis to determine the final model. Simulated and real examples are used to illustrate the analysis.