Message-ID: <dt4r3c$gma$1@sea.gmane.org>
Date: 2006-02-17T15:45:44Z
From: Frank Samuelson
Subject: using kernel density estimates to infer mode of distribution
In-Reply-To: <20060216102841.0997c0b4.azzalini@stat.unipd.it>
A density() fit calls the eval x and estimate y:
fit<-density(data)
plot(fit$x,fit$y)
Adelchi Azzalini wrote:
> On Wed, 15 Feb 2006 18:28:25 -0500, Dan Rabosky wrote:
>
> DR>
> DR> Is it possible to use "density" or another kernel density
> DR> estimator to identify the mode of a distribution? When I use
> DR> 'density', the resulting
>
> a simple option is of the form
> fit$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