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0下载：
An AutoRegressive Moving Average Spectral Analysis toolbox for use with Matlab.-An AutoRegressive Moving Average Spectra l Analysis toolbox for use with Matlab.
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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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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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Calculates adaptive autoregressive (AAR) and adaptive autoregressive moving average estimates (AARMA)of real-valued data series using Kalman filter algorithm.
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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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ARIMA模型全称为自回归积分滑动平均模型(Autoregressive Integrated Moving Average Model,简记ARIMA)，是由博克思(Box)和詹金斯(Jenkins)于70年代初提出一著名时间序列预测方法[1] ，所以又称为box-jenkins模型、博克思-詹金斯法。其中ARIMA（p，d，q）称为差分自回归移动平均模型，AR是自回归， p为自回归项； MA为移动平均，q为移动平均项数，d为时间序列成为平稳时所做的差分次数。所谓ARIMA模型，是指将非平稳
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2下载：
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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