This article issues a new viewpoint and method in modeling for time series based on ar model. The method is able to give less calculating and to be programmed on computer.
提出了基于自回归(AR)模型对时间序列统一建模的新观点和方法，可大大减少计算量，并在微机上编程实现。
In this paper a new method of modeling forecasting is given for the time series by using the numerical solution of differential equation.
本文利用微分方程的数值解法对时间序列建模预测作了新的尝试。
Stationary time series state space modeling method for the analysis of the transition process gyro.
将非平稳时间序列的状态空间建模方法用于陀螺过渡过程的分析。
Although the period of using ar, MR, ARMA, ARIMA modeling methods of time series analysis for observed seismic data processing is not long, it is believed that these methods are promising.
时间序列分析中的AR,MR,ARMA,ARIMA等建模方法应用于地震观测资料分析中尚为时不长，是很有发展前途的地震信息处理方法。
A state space approach for the modeling of nonstationary time series is presented.
非平稳时间序列的状态空间建模技术被用于陀螺漂移分析。
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 new neural tree for modeling the time-series forecasting is proposed in the paper.
提出了一种新的神经树模型来进行时间序列预测。
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。
By using the data modeling methods of time series analysis, we can build the model of bias instability for the drift data of fiber optic gyro.
但通过时间序列分析中的数据建模方法可对光纤陀螺的零漂测试数据建立零偏稳定性数学模型。
The application of time-series modeling and forecasting method to the spectral analysis for lubricating oil of mechanical equipment is discussed.
讨论了时序建模与预测方法在机械设备滑油光谱分析中的应用。
In this paper a new method of modeling forecasting is given for the time series by using the numerical solution of differential equation. A practical example is also given.
本文利用微分方程的数值解法对时间序列建模预测作了新的尝试。文中用实例给以说明。
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。
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。
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