A mixed autoregressive moving average (MARMA) model is proposed for modeling nonlinear time series.
提出了一类用于非线性时间序列建模的混合自回归滑动平均模型(MARMA)。
The Support Vector Regression(SVR)is used for the time series analysis and prediction to resolve the complex nonlinear system modeling problems.
用支持向量回归（SVR）的方法分析和预测时间序列，可解决复杂非线性系统的建模问题。
We obtain some results as follows:In chapter 2, a new mixture autoregressive moving average model is proposed for modeling nonlinear time series.
提出了一类新的用于非线性时间序列建模的混合自回归滑动平均模型。
In this paper a variety of time series nonlinear models are introduced and the idea and modeling method of the threshold autoregression are discussed in detail.
本文概述了时序分析的非线性模型类，详细叙述了门槛自回归模型的建模思想和方法。
In this paper a variety of time series nonlinear models are introduced and the idea and modeling method of the threshold autoregression are discussed in detail.
本文概述了时序分析的非线性模型类，详细叙述了门槛自回归模型的建模思想和方法。
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