Message-ID: <20060216102841.0997c0b4.azzalini@stat.unipd.it>
Date: 2006-02-16T09:28:41Z
From: Adelchi Azzalini
Subject: using kernel density estimates to infer mode of distribution
In-Reply-To: <5.2.1.1.2.20060215172856.0127c948@postoffice9.mail.cornell.edu>
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 <azzalini at stat.unipd.it>
Dipart.Scienze Statistiche, Universit?? di Padova, Italia
tel. +39 049 8274147, http://azzalini.stat.unipd.it/