Also look at ecdf() from package "stepfun".
HTH,
Jerome Asselin
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On September 10, 2003 04:03 pm, Kevin S. Van Horn wrote:
>
> Your method looks like a naive reimplementation of integration, and
> won't work so well for distributions that have the great majority of the
> probability mass concentrated in a small fraction of the sample space.
> I was hoping for so
Your method looks like a naive reimplementation of integration, and
won't work so well for distributions that have the great majority of the
probability mass concentrated in a small fraction of the sample space.
I was hoping for something that would retain the adaptability of
integrate().
(Ted
On 09-Sep-03 Kevin S. Van Horn wrote:
> Given f, a pdf over a finite interval, is there any existing R function
> that
> can efficiently tabulate the cumulative distribution function for f, or
> produce all N+1 quantiles of the form i/N? "Efficiently" here means
> better than doing repeated integ
Perhaps approx() or approxfun() can help you create an efficient CDF.
HTH,
Jerome
On September 9, 2003 01:38 pm, Kevin S. Van Horn wrote:
> Content-Length: 417
> Status: R
> X-Status: N
>
> Given f, a pdf over a finite interval, is there any existing R function
> that can efficiently tabulate th
