David Winsemius
On Mar 25, 2009, at 9:30 AM, Pradeep Raje wrote:
> Dear all:Request your indulgence. The econophysics gurus do this
> stuff all
> the time: all their PDFs are smooth, with neat log x axis.
> 1. The kernel density estimate (KDE) function returns the empirical
> probability density at 2^n points (min: 512). The big question is
> how do I
> scale back the x-values (say, density$x) to x-values in terms of the
> original dataset?
> 2. To give you a concrete idea, i have a dataset of 3471 obs (x=date
> index,
> y=parameter values). Now the density estimate d<-density(x) gives be
> 2048
> x-values. When I plot the PDF, the x axis is obviously d$x,
> length=2048.
> 3. How can I scale back these 2048 values to get a sense of calendar
> time
> (original date index)?
> 4. Subsidiary question is: how do i bring in the remaining values
> (3471-2048)?
You seem to have the idea that the original data is "lined up" with
the density estimates. That is not so.
>
> Thanks very much in advance.
> pradeep
>
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>
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT