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- For multiple stationary time series Granger causality tests and vector autoregressive models are presented. 多平稳时间序列，"格兰其"成员因果律测试和自回归模式给的矢量。
- After the trend extraction, the method of time series analysis is used to make the autoregressive moving average (ARMA) model for stationary time series. 在成功提取趋势项后,通过采用时间序列的分析方法,建立了陀螺漂移平稳时间序列的自回归滑动平均模型;
- The killing probability expressions and statistical property of the stationary time series are obtained, and their relative formulae under different shotting characteristics are given. 给出滞留射击方式下滞留时间序列毁伤概率及统计特性的数学描述，并得到不同射击特性下的相关计算公式。
- Multivariate stationary time series model 多元平稳时序模型
- Analysis and application of stationary time series method 平稳时间序列法的分析和应用
- Gyroscope Drift Forecasting Based on Stationary Time Series Analysis 基于平稳时间序列分析方法的陀螺漂移预测
- The spectral density estimation of stationary time series with missing data 漏缺数据平稳时间序列下的谱密度估计
- The equation is split into an Euler equation and a non stationary Stokes equation within each time step. 在每一个时间步方程分离为一个Euler方程和一个非定常的Stokes方程。
- A method for estimating the matching performance of TERCOM map under non stationary terrain is proposed. 提出了一种非平稳地形中TERCOM地图匹配性能的估计方法。
- stationary time series 固定时间序列
- The Hawking effect,event horizon and corresponding temperature of a uniformly accelerating,non stationary,charged black hole are given. 给出了匀加速荷电黑洞的Hawking效应和事件视界及相应温度。
- non- stationary time series 非平稳时间序列
- The network traffic is validated to possess a non stationary characteristic and the simulated network traffic is adopted to approximate the AAR model. 验证了流量信号的非平稳特性，并采用模拟获取的网络流量拟合AAR模型。
- This is called a deseasonalizing time series. 这叫调和时间数列。
- Time Series Analysis Hamilton J.D. 时间序列分析。
- Predicts the future values for a time series. 预测一个时序的未来值。
- Selecting the advanced Eddington coordinates and adopting the thin film brick wall model, we calculate the entropy of the straightly accelerating non stationary black hole expressed by Kinnersley metric. 选取超前爱丁顿坐标 ;采用薄膜brick wall模型 ;计算Kinnersley度规表述的直线加速运动动态黑洞的熵 .
- Results A new mode of time series is established. 结果建立了一个新的时间序列模型。
- By using the function of wavelet multi 梥cale analysis,the non -stationary time series of the housing mean price can be divided into main trend part and detail part. 利用小波多尺度分析的功能,将非平稳时间序列的住宅房产均价分解成主要趋势和细节两大部分。
- After the time series fuzzy fractal processing of the mine gas emission quantity, the non linear relations of the influence factors were combined with BP neural network. 通过对矿井瓦斯涌出量时间序列的模糊分形处理,用BP神经网络对影响因素间的非线性关系进行拟合。
