We investigate some probabilistic properties of a new class of nonlinear time series models. A sufficient condition for the existence of a unique causal, strictly and weakly stationary solution is derived. To understa...We investigate some probabilistic properties of a new class of nonlinear time series models. A sufficient condition for the existence of a unique causal, strictly and weakly stationary solution is derived. To understand the proposed models better, we further discuss the moment structure and obtain some Yule-Walker difference equations for the second and third order cumulants, which can also be used for identification purpose. A sufficient condition for invertibility is also provided.展开更多
在分析AR模型的Y u le-W a lker方程和对称矩阵分解理论的基础上,提出基于对称矩阵分解理论的AM模型算法.该算法研究有关AR模型阶数p的选择,讨论AR模型的其它求法.仿真结果表明,改进算法的AR参数能有效提高频谱分辨率、改善方差性能、...在分析AR模型的Y u le-W a lker方程和对称矩阵分解理论的基础上,提出基于对称矩阵分解理论的AM模型算法.该算法研究有关AR模型阶数p的选择,讨论AR模型的其它求法.仿真结果表明,改进算法的AR参数能有效提高频谱分辨率、改善方差性能、提高频谱估计的精度.展开更多
基金supported by the Fundamental Research Funds for the Central Universities of China (Grant No. 2010121005)supported by the Scientific Research and Development Funds for Youth of Fujian University of Technology of China (Grant No. GY-Z09081)
文摘We investigate some probabilistic properties of a new class of nonlinear time series models. A sufficient condition for the existence of a unique causal, strictly and weakly stationary solution is derived. To understand the proposed models better, we further discuss the moment structure and obtain some Yule-Walker difference equations for the second and third order cumulants, which can also be used for identification purpose. A sufficient condition for invertibility is also provided.
