Orange: Moving Transform

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.

• 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.

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

Referensi

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

Pranala Menarik

• Orange