搜索资源列表
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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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股票交易预测 k线图绘制 5日均线，10日均线，20日均线，60日均线 计算,Stock forecast mapping k line 5 average, 10 average, 20 average, 60 days moving average calculation
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3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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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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matlab 高频算法交易实现, 附有详细说明文档，包括从基础的均线到高级的遗传算法在内的实现，非常实用-matlab frequency algorithmic trading, with detailed documentation, including moving average based on advanced genetic algorithm, including the realization of very practical
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信号的平滑处理，moving average算法，Mablab源程序-signal processing, moving average algorithm, in Mablab
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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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Sliding Sum Averaging Filter
Smoothes data by sliding it past itself, one sample at a time, and summing.
The length of the output is the same as the length of the input. The output
will be normalized. Equivalent to a moving average (lowpass
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averaging filter moving average filter
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moving average filter matlab implementation
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moving average filter using widey as low filter in matlab
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卡夫曼自适应移动平均线MATLAB代码
SMA：Simple MA 简单平均线
EMA：Exp MA指数平均线
AMA：Adaptive MA 卡夫曼自适应移动平均
算法过程
卡夫曼自适应移动平均算法过程整理
对比测试代码(测试数据使用HS300指数，数据直接从Yahoo上下载)：-Kaufman adaptive moving average MATLAB code
SMA: Simple MA Simple Average
EMA: Ex
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Moving average code as a filter to smooth the graph in matlab
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本代码是在用MATLAB做预测时用到的，分别为预测模型为移动平均值模型、指数平滑预测法、季节指数预测法-This code is used when using MATLAB to do prediction, forecasting model respectively for the moving average model and exponential smoothing prediction method
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计算移动平均hurt指数，用MATLAB的程序代码，适合初学者(Moving average hurt index)
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matlab程序实现滑动平均滤波（MAF）(Moving average filtering (MAF) implemented by MATLAB program)
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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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数字信号处理技术之移动平均滤波器的设计（The Scientist and Engineer's Guide to Digital Signal Processing）(Digital signal processing technology, mobile average filter)
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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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