using kernel density estimates to infer mode of distribution

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  <azzalini at stat.unipd.it>
Dipart.Scienze Statistiche, Universit?? di Padova, Italia
tel. +39 049 8274147,  http://azzalini.stat.unipd.it/