Moving Average

This node calculates the moving average of a column. The moving average values are displayed in a new column appended at the end of the table or (if selected) replaces the original columns. For all window based methods (Backward/Center/Forward simple/Gaussian, Harmonic Mean) the cells that do not have a complete window (final at the beginning and the end of the table) are filled with Missing Values.

Options

Type of Moving Average

Select the moving average method defining how values in the window are weighted (backward, centered, forward, Gaussian, cumulative, exponential variants, harmonic mean, etc.).
For the Gaussian weighted moving average the individual values are weighted based on the position in the window.

gauss(i,mean,std_dev) = Math.exp((-0.5) * (i - mean) * (i - mean) / std_dev^2)

std_dev = (k - 1) / 4

For the exponential moving average the individual values are weighted as

alpha = 2/(k+1)

• Backward simple:

  Backward_simple_n = 1/k * sum{v_n-(k-1) ... v_n}

• Center simple:

  Center_simple_n = 1/k * sum{v_n-(n-1)/2 ... v_n ... v_n+(n-1)/2}

• Forward simple:

  Forward_simple_n = 1/k * sum{v_n ... v_n+k-1}

• Backward Gaussian:

  Backward_gaussian_n = sum{i = 0 ... k-1} gauss(i,k-1,std_dev)*v_n-i

• Center Gaussian:

  Center_gaussian_n = sum{i = 0 ... k-1} gauss(i,(k-1)/2,std_dev)*v_n+(i-(k-1)/2)

• Forward Gaussian:

  Forward_gaussian_n = sum{i = 0 ... k-1} gauss(i,0,std_dev)*v_n+i

• Harmonic Mean Center: The harmonic mean can only be used for strictly positive values.

  Center_harmonic_n = n/{sum{i = 0 ... k-1} 1/v_n+(i-(k-1)/2)

• Cumulative simple:

  Cumulative_n= 1/n * sum{v_0 ... v_n-1}

• Simple exponential:

  Simple_exponential_0 = v_0

  EMA(v,n) = Simple_exponential_n = alpha*v_n + (1-alpha)*Simple_exponential_n-1

• Double exponential:

  Double_exponential_n = 2 * EMA(v,n) - EMA(EMA(v,n),n)

• Triple exponential:

  Triple_exponential_n = 3 * EMA(v,n) - 3 * EMA(EMA(v,n),n) + EMA(EMA(EMA(v,n),n),n)

• Old exponential:

  Exponential_n = alpha*v_n + (1-alpha) * Backward_simple_n-1

Window length

Number of consecutive rows used to compute each moving average. Must be an odd number for centered methods.

Remove original columns

If checked, the selected input columns are replaced by their moving average. If unchecked, new columns named MA(<column>) are appended.

Column selection

Select the numeric (double compatible) columns for which to compute moving averages. Move columns of interest to the "Includes" list.

Views

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Workflows

• 01_Data_PreparationKNIME Hub
• 01_Data_PreparationKNIME Hub
• 01_Example_of_Time_Series_FunctionalityKNIME Hub
• 01_Example_of_Time_Series_FunctionalityKNIME Hub
• 01_Guided_VisualizationKNIME Hub
• Show all 177 workflows

Links

• Need help (very new to this field)by ipazin on 2019-03-11

  forum.knime.com/p/55946
• Choice for time series loopingby HansS on 2019-11-21

  forum.knime.com/p/75296

Developers