Nonparametric autoregressive model have gained much attention recently, due primarily to the fact that they can describe some nonlinear features exhibited by many data itself in applications.
非参数自回归模型因其能够描述许多数据自身所体现的非线性特征而受到人们的广泛关注。
Threshold autoregressive model (TAR) is a nonlinear sequential model which is segmentedly linear.
门限自回归模型（TAR）是一种分段线性的非线性时间序列模型。
This paper presents a nonlinear autoregressive exogenous (NARX) model to approximate dynamics of crankshaft speed with the mass of the idle feeding fuel and the spark advance.
本文采用一类非线性自回归模型(NARX)，描述怠速过程中怠速供油量、点火提前角与曲轴转速之间的关系。
The results validate more validity of nonlinear error correction model on the wavelet neural network than linear vector autoregressive model, and forecast validly the nonlinear economy system.
研究证明，小波神经网络所建立的非线性误差校正模型有较好的预测效果，能够有效地预测非线性经济系统。
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。
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)。
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)。
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