# using kernel density estimates to infer mode of distribution

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## using kernel density estimates to infer mode of distribution

 Hello... Is it possible to use "density" or another kernel density estimator to identify the mode of a distribution?  When I use 'density', the resulting density plot of my data is much cleaner than the original noisy histogram, and I can clearly see the signal that I am interested in.  E.g., suppose my data is actually drawn from two or more normal (or other) distributions.  Looking at the kernel density plots, it seems that the estimator gives a good approximation of the modal values of each distribution, but I can't figure out how to obtain these values short of visually estimating the location of the mode using the plot(density). Is there a relatively easy way to do this? Thanks in advance for your help! Dan Rabosky Dan Rabosky Department of Ecology and Evolutionary Biology Cornell University Ithaca, NY14853-2701 USA web: http://www.birds.cornell.edu/evb/Graduates_Dan.htm______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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## Re: using kernel density estimates to infer mode of distribution

 On Wed, 15 Feb 2006 18:28:25 -0500, Dan Rabosky wrote: DR> DR>  Is it possible to use "density" or another kernel density DR>  estimator to  identify the mode of a distribution?  When I use DR>  'density', the resulting a simple option is of the form    fit\$eval[fit\$estimate==max(fit\$estimate)] assuming that fit\$eval is the vector of evaluation points, and fit\$estimate the corrisponding density estimates (this is the sort of output produced by sm.density) Here I have assumed there is single mode and we are in the scalar case, for simplicity. Some variant required in the more general case. best regards, Adelchi Azzalini -- Adelchi Azzalini  <[hidden email]> Dipart.Scienze Statistiche, Università di Padova, Italia tel. +39 049 8274147,  http://azzalini.stat.unipd.it/______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html