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It would be great to have an implementation of an algorithm that finds modes of kernel density estimates. Most common algorithm is mean-shift algorithm:
Comaniciu, Dorin; Peter Meer (May 2002). "Mean Shift: A Robust Approach Toward Feature Space Analysis". IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE) 24 (5): 603–619. doi:10.1109/34.1000236.
I think it would be useful to have in this package, though I don't really have time to do it myself in the near future. If you want to open a pull request, I'd be happy to look over it.
I made a pull request for this at Clustering.jl (JuliaStats/Clustering.jl#43). If people want to find peaks of a kernel density estimate they can use the code there.
It would be great to have an implementation of an algorithm that finds modes of kernel density estimates. Most common algorithm is mean-shift algorithm:
Comaniciu, Dorin; Peter Meer (May 2002). "Mean Shift: A Robust Approach Toward Feature Space Analysis". IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE) 24 (5): 603–619. doi:10.1109/34.1000236.
A great short (2 page) guide to using mean shift algorithm for clustering http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/TUZEL1/MeanShift.pdf
Might be more appropriate for the Clustering.jl package.
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