Orange: Moving Transform

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Sumber: https://orange.biolab.si/widget-catalog/time-series/moving_transform/


Apply rolling window functions to the time series. Use this widget to get a series’ mean.

Input

Time series: Time series as output by As Timeseries widget.

Output

Time series: The input time series with the added series’ transformations.

In this widget, you define what aggregation functions to run over the time series and with what window sizes.

Moving-transform-stamped.png
  • Define a new transformation.
  • Remove the selected transformation.
  • Time series you want to run the transformation over.
  • Desired window size.
  • Aggregation function to aggregate the values in the window with. Options are: mean, sum, max, min, median, mode, standard deviation, variance, product, linearly-weighted moving average, exponential moving average, harmonic mean, geometric mean, non-zero count, cumulative sum, and cumulative product.
  • Select Non-overlapping windows options if you don’t want the moving windows to overlap but instead be placed side-to-side with zero intersection.
  • In the case of non-overlapping windows, define the fixed window width(overrides and widths set in (4).

Example

To get a 5-day moving average, we can use a rolling window with mean aggregation.

Moving-transform-ex1.png

To integrate time series’ differences from Difference widget, use Cumulative sum aggregation over a window wide enough to grasp the whole series.

Moving-transform-ex2.png


Referensi

Pranala Menarik