I was thinking it should offer a randomized version (taking a generator),
since randomized median algorithms provide the best expected performance.
It could also offer a deterministic version using some variant of
median-of-medians, intended for long lists. I guess it probably should
retain the naive version for short lists. Some benchmarking would suggest a
good cutoff. Has anyone come up with a better practical deterministic O(n)
algorithm since median-of-medians? I saw a paper by Dorit Dor on reducing
the number of comparisons to a bit under 3n, which also showed a lower
bound of a bit over 2n, but the algorithm she gives strikes me as far too
complex to be practical.
On Sep 1, 2012 9:17 PM, "Gershom Bazerman"
In my experience, doing much better than the naive algorithm for median is surprisingly hard, and involves a choice from a range of trade-offs. Did you have a particular better algorithm in mind?
If you did, you could write it, and contact the package author with a patch.
You also may be able to find something of use in Edward Kmett's order-statistics package: http://hackage.haskell.org/** package/order-statisticshttp://hackage.haskell.org/package/order-statistics
Cheers, Gershom
On 9/1/12 3:26 PM, David Feuer wrote:
The median function in the hstats package uses a naive O(n log n) algorithm. Is there another package providing an O(n) option? If not, what would it take to get the package upgraded?
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