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The easiest way to store speed statistics as a rolling average, with fields
count, mean
In this case, every time a new speed is detected which matches the key, count = count+1 and mean=((mean*count)+newSpeed)/(count+1). That's simple enough.
But what if we want to know the distribution of speeds? How can we update such a distribution incrementally?
The text was updated successfully, but these errors were encountered:
One straightforward way is to just store histograms in arrays, with each element in the array being a bin of 1 kph, 5kph or whatever. When a new measurement comes in you increment the corresponding bin. If this turns out to be too voluminous the usual combination of delta coding / variable byte coding / run length coding should compress this down nicely.
The plan is to digest GPS point updates into speed statistics for way segments. The statistics will be keyed to:
The easiest way to store speed statistics as a rolling average, with fields
In this case, every time a new speed is detected which matches the key,
count = count+1
andmean=((mean*count)+newSpeed)/(count+1)
. That's simple enough.But what if we want to know the distribution of speeds? How can we update such a distribution incrementally?
The text was updated successfully, but these errors were encountered: