Work with Irregular Time Series
Draw a sample of Poisson process, sampled at the random times of arrivals.
Out[1]= | ![](HTMLImages.en/work-with-irregular-time-series/O_15.png) |
Out[2]= | ![](HTMLImages.en/work-with-irregular-time-series/O_16.png) |
Visualize the time series.
Out[3]= | ![](HTMLImages.en/work-with-irregular-time-series/O_17.png) |
Use TimeSeriesMapThread to subtract the mean function from the time series.
Out[5]= | ![](HTMLImages.en/work-with-irregular-time-series/O_18.png) |
Use MovingMap to compute mean over a centered constant‐width sliding window.
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Out[7]= | ![](HTMLImages.en/work-with-irregular-time-series/O_19.png) |
Use TimeSeriesAggregate to build regularly spaced time series of the largest values in non-overlapping windows of constant width.
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Out[9]= | ![](HTMLImages.en/work-with-irregular-time-series/O_20.png) |
Out[10]= | ![](HTMLImages.en/work-with-irregular-time-series/O_21.png) |
Resample with a step of 10 using interpolation of order 0.
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Out[12]= | ![](HTMLImages.en/work-with-irregular-time-series/O_22.png) |
Out[13]= | ![](HTMLImages.en/work-with-irregular-time-series/O_23.png) |
Treat the original time series as regularly sampled for use in functions that require such uniformly sampled input.
Out[14]= | ![](HTMLImages.en/work-with-irregular-time-series/O_24.png) |
Out[15]= | ![](HTMLImages.en/work-with-irregular-time-series/O_25.png) |
Out[16]= | ![](HTMLImages.en/work-with-irregular-time-series/O_26.png) |