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For our application, I'm trying to find a memory-efficient, incremental algorithm to maintain variance of geometric mean.

This "online algorithm" on Wikipedia seems excellent,

http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance

however, I'm not sure if / how I can apply the same idea to geometric mean / variance.

Numerical stability is preferred, but probably not strictly necessary as our samples have limited precision - the range is between 1ms and 30,000ms (timeout - trim value) as integer, in lognormal distribution. Sample data are actually web site response time observed periodically BTW.

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    I'm not sure about M(2,n) though. sum of squares of differences will be log(x / geometric mean)^2 rather than (x - mean)^2 correct? No idea what the new recurrence equation for M(2,n) will be...2012-10-04

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