Computing inverse cdf (quantile function) from a KDE

If you are going to be doing a lot of this then you might want to
consider using logspline density estimates (logspline package) instead
of kernel density estimates.
Hello,

I wanted to know if there is a simple way of getting the inverse cdf for a
KDE estimate of a density (using the ks or KernSmooth packages) in R ?

The method I'm using now is to perform a numerical integration of the pdf
to get the cdf and then doing a search for the desired probablity value,
which is highly inefficient and very slow.

Thanks,
-fj

        [[alternative HTML version deleted]]

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Gregory (Greg) L. Snow Ph.D.
538280 at gmail.com

Computing inverse cdf (quantile function) from a KDE

Thread (3 messages)