[R] density function

[Greg Snow]

Here are 2 approaches:

Use logspline density estimates (logspline package) rather than kernel
density estimates, this can give you a function to pass to integrate
or other tools, the estimates may be a little different from the
kernel density estimates.

If you need to use kernel density estimates, then realize that the kde
is just the sum of 1/n times the kernel centered at each of the n
points.  And the integral of a sum is the sum of the integrals (and
the 1/n can be factored out), so you can just integrate each of the n
kernals (centered at the datapoints with proper width), then sum and
divide by n (or take the mean).

On Tue, Jun 26, 2012 at 6:13 PM, pilaw <pilawski.p at gmail.com> wrote:
> Hello,
>
> I need density function so that I can find expected value (using
> integration). I use density():
> f= density(data)
> but f isn't a function and I can't get values and integrate it
> This is very urget, so please help.
>
> Greetings
> Peter
>
> --
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-- 
Gregory (Greg) L. Snow Ph.D.
538280 at gmail.com