Performs exponential average on a univariate or multivariate (vector) time series. This VI returns a smoothed time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.


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Inputs/Outputs

  • c2ddbl.png Xt —

    Xt specifies the multivariate (vector) time series. Each column of the 2D array represents a vector at certain time.

  • c1du16.png exponential type —

    exponential type specifies the type of exponential average. Each element of the array is one selection for one channel.

  • c1dnclst.png exponential factors —

    exponential factors specifies the weighting factors for exponential smoothing. Each element of the array represents one selection for one channel.

  • cdbl.png level —

    level specifies the weight for the level cumulant. The value must be a number between 0 and 1.

  • cdbl.png trend —

    trend specifies the weight for the trend cumulant. The value must be a number between 0 and 1. This option is available only when exponential type is Double or Triple.

  • cdbl.png season —

    season specifies the weight for seasonal cumulant. The value must be a number between 0 and 1. This option is available only when exponential type is Triple.

  • cerrcodeclst.png error in (no error) —

    error in describes error conditions that occur before this node runs. This input provides standard error in functionality.

  • c1di32.png season period —

    season period specifies the length of the seasonal pattern in the input time series. Each element of the array represents one selection for one channel. This option is available only when exponential type is Triple.

  • c1du16.png season type —

    season type specifies the way in which this VI models the seasonality. Each element of the array represents one selection for one channel. This option is available only when exponential type is Triple.

  • i2ddbl.png Xt averaged —

    Xt averaged returns the averaged multivariate (vector) time series. Each column of the 2D array represents a vector at certain time.

  • ierrcodeclst.png error out —

    error out contains error information. This output provides standard error out functionality.

    • TSA Exponential Average Details

    This VI uses the exponential weighting scheme to produce a smoothed time series. This VI computes the averaged values by assigning exponentially decreasing weights to the old values in the original time series according to the following equation:

    Xa(i) = aXt(i-1) + a(1-a)Xt(i-2) + a(1-a)²Xt(i-3) +…

    where a is the level weight for level cumulant Xa, Xa is the averaged time series, and Xt is the original time series.

    Examples

    Refer to the Exponential Smoothing VI in the labview\examples\Time Series Analysis\TSAGettingStarted directory for an example of using the TSA Exponential Average VI.