using kernel density estimates to infer mode of distribution
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