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ExponentialMovingAverage[list,α]

给出 list 的指数移动平均数，带有平滑常数 α.

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Details and Options Details and Options
范例  
基本范例  
范围  
推广和延伸  
应用  
属性和关系  
参见
相关指南
历史
按以下格式引用：

ExponentialMovingAverage

ExponentialMovingAverage[list,α]

给出 list 的指数移动平均数，带有平滑常数 α.

更多信息

范例

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基本范例  (2)

符号形式的指数移动平均数：

Wolfram Language code: ExponentialMovingAverage[{a, b, c}, x]

用于数值的指数移动平均数：

Wolfram Language code: ExponentialMovingAverage[Range[10], 1 / 3]

范围  (4)

以机器精度计算指数移动平均数：

Wolfram Language code: ExponentialMovingAverage[N[{1, 5, 7, 3, 6, 2}], 1 / 2]

矩阵的指数移动平均数为矩阵：

Wolfram Language code: data = RandomReal[5, {10, 2}]
Wolfram Language code: ExponentialMovingAverage[data, 1 / 4]

获得任意精度的列表结果：

Wolfram Language code: ExponentialMovingAverage[N[{1, 5, 7, 3, 6, 2}, 25], 1 / 2]

获得任意精度的平滑系数的结果：

Wolfram Language code: ExponentialMovingAverage[{1, 5, 7, 3, 6, 2}, N[1 / 2, 30]]

推广和延伸  (2)

计算一个 SparseArray 结果：

Wolfram Language code: sp = SparseArray[{{i_, i_} :> i, {i_, j_} /; j == i + 1 :> i - 1}, {100, 10}]
Wolfram Language code: ExponentialMovingAverage[sp, 1 / 10]

计算 TemporalData 对象的结果：

Wolfram Language code: td = TemporalData[{1, 2, 3}, {0}]
Wolfram Language code: ExponentialMovingAverage[td, 1 / 2]
Wolfram Language code: Normal[%]

应用  (3)

光滑噪声数据：

Wolfram Language code: data = Range[20] + RandomReal[{-2, 2}, 20]
Wolfram Language code: smoothed = ExponentialMovingAverage[data, 1 / 4]
Wolfram Language code: ListPlot[{data, smoothed}, PlotLegends -> {"data", "smoothed"}]

用初始值计算一个指数移动平均数：

Wolfram Language code: data = Range[20] + RandomReal[{-2, 2}, 20]
Wolfram Language code: start = 4.5;
Wolfram Language code: smoothed = Rest[ExponentialMovingAverage[Join[{start}, data], 1 / 5]]
Wolfram Language code: ListPlot[{data, smoothed}, PlotLegends -> {"data", "smoothed"}]

计算一个金融时间序列的指数移动平均数：

Wolfram Language code: ListLinePlot[ExponentialMovingAverage[FinancialData["GE", "Jan. 1, 2000", "Value"], 0.1]]

属性和关系  (3)

一个指数移动平均数的项满足递推关系：

Wolfram Language code: data = RandomReal[10, 100];
Wolfram Language code: alpha = 3 / 4;
Wolfram Language code: ema = ExponentialMovingAverage[data, alpha];
Wolfram Language code: Rest[ema] == Most[ema] + alpha(Rest[data] - Most[ema])

平滑系数是 0 的指数移动平均数是一个常数：

Wolfram Language code: ExponentialMovingAverage[{a, b, c, d}, 0]

平滑系数是 1 的指数移动平均数是一个基本列表：

Wolfram Language code: ExponentialMovingAverage[{a, b, c, d}, 1]
Wolfram Research (2007)，ExponentialMovingAverage，Wolfram 语言函数，https://reference.wolfram.com/language/ref/ExponentialMovingAverage.html.

文本

Wolfram Research (2007)，ExponentialMovingAverage，Wolfram 语言函数，https://reference.wolfram.com/language/ref/ExponentialMovingAverage.html.

CMS

Wolfram 语言. 2007. "ExponentialMovingAverage." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/ref/ExponentialMovingAverage.html.

APA

Wolfram 语言. (2007). ExponentialMovingAverage. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/ref/ExponentialMovingAverage.html 年

BibTeX

@misc{reference.wolfram_2026_exponentialmovingaverage, author="Wolfram Research", title="{ExponentialMovingAverage}", year="2007", howpublished="\url{https://reference.wolfram.com/language/ref/ExponentialMovingAverage.html}", note=[Accessed: 16-October-2026]}

BibLaTeX

@online{reference.wolfram_2026_exponentialmovingaverage, organization={Wolfram Research}, title={ExponentialMovingAverage}, year={2007}, url={https://reference.wolfram.com/language/ref/ExponentialMovingAverage.html}, note=[Accessed: 16-October-2026]}