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I want to estimate percentile statistics for time-series pairs $(t, y)$ over varying granularities of time (hour, day, month, etc)

For example, if I have the following pairs (10:59, 3), (11:01, 2), (11:32, 5), the first point is part of a different hour window, but all three are part of the same day window.

When a new point arrives, I am recomputing the hour window statistics directly, by iterating over all data points in the window. Unfortunately, this does not scale to the longer time windows.

Is there a way to incrementally update the statistics for the longer time windows?

accounted4
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  • Welcome to CV. We might already have an answer: could you explain how your problem differs, if at all, from the one discussed at https://stats.stackexchange.com/questions/7959? – whuber Feb 17 '20 at 21:46
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    Thanks! I think that answers it. – accounted4 Feb 18 '20 at 22:13

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