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2下载：
计算ARMA(p，q)模型的功率谱密度。
形参说明：
b——双精度实型一维数组，长度为(q+1),存放ARMA(p，q)模型的滑动平均系数。
a——双精度实型一维数组，长度为(p+1),存放ARMA(p,q)模型的自回归系数。
q——整型变量,ARMA(p,q)模型的滑动平均阶数。
p——整型变量,ARMA(p,q)模型的自回归阶数。
sigma2——双精度实型变量,ARMA(p,q)模型白噪声激励的方差。
fs——双精度实型变量,采样频率(Hz)。
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基于受控自回归积分滑动平均 (CARIMA)模型控对象的预测控制程序,Points based on the controlled auto-regressive moving average (CARIMA) Model Predictive Control control procedures
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运用自回归滑动平均模型进行预测的matlab
程序,The use of autoregressive moving average model to predict the matlab program
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在matlab的环境下实现了自回归移动平均模型（arima）,Matlab environment in the realization of the auto-regressive moving average model (arima)
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自回归移动平均模型(Autoregressive Integrated Moving Average Model)的Matlab实现,时间序列分析代码-Autoregressive moving average model (Autoregressive Integrated Moving Average Model) to achieve the Matlab
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基于MATLAB的ARIMA模型的源代码。ARIMA模型是自回归滑动平均求和模型，是时间序列分析模型，可以用于时间序列的预测。该代码实现了ARIMA模型的建模和谱分析过程-The ARIMA model based on MATLAB source code. ARIMA model is the sum of autoregressive moving average model is time series analysis models, can be used for time seri
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Adaptive Mean-AutoRegressive-Moving-Average model estimation
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autoregressive moving average model grade 1,1
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模型包括三种基本类型：自
回归模型、移动平均模型和
自回归移动平均模型
-The model consists of three basic types: the regression model, moving average and autoregressive moving average model
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Parameter identifi cation for a single-degree-of-freedom
system using autoregressive moving average model:
Application to cutting system
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Parameter identifi cation for a singledegreeoffreedom
system using autoregressive moving average model
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arma（自回归滑动平均模型）的fortran程序-fortran program arma (autoregressive moving average model)
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Matlab计算自回归滑动平均模型参数，自回归滑动模型-Matlab autoregressive moving average model parameters
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ARMA model is auto-regressive Moving Average model in statistical signal processing.
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对于自回归滑动平均模型进行参数辨识，并对白噪声进行方差估计。运算结果具有良好的收敛性，可推广为模型辨识的通式-For auto-regressive moving average model parameter identification, and white noise variance estimation. Operation result has a good convergence, can be extended to model identification formula
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受控自回归滑动平均模型的梯度迭代算法，经过多次迭代计算之后，能够有效的逼近真实值-Controlled autoregressive moving average model of gradient iterative algorithm, after several iterations, can effectively approach the true value
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ARIMA模型全称为差分自回归移动平均模型(Autoregressive Integrated Moving Average Model,简记ARIMA)，-ARIMA is。。。。。
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Parameter identification for a single-degree-of-freedom system using autoregressive moving average model: Application to cutting system
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一个量化择时的模型 用5日12日效果比较好-Double moving average model
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自回归滑动平均模型，能很好地建立随机风速模型，产生随机序列。用于电力系统可靠性分析。-Autoregressive moving average model, stochastic wind energy is well established model, generate a random sequence. Power system reliability analysis.
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