[R] using kernel density estimates to infer mode of distribution

[Frank Samuelson]

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