[R] Percentile Estimation From Kernel Density Estimate
Karl Ove Hufthammer
Karl.Hufthammer at math.uib.no
Mon Jul 28 11:18:13 CEST 2008
Jeffrey_Bromaghin at fws.gov:
> Has anyone developed a defensible method of estimating percentiles from a
> univariate kernel density estimate? I am working on a problem in which
> the density estimate is of interest, but I would also like to estimate the
> value of the variable for which the distribution was, say, 0.20. I spent
> some time searching the archives and found some message from 2006 that
> implied such a method was not available at that time.
You could always use simple numerical integration do this. Something like
x = rnorm(1000)
d = density(x, n=10^4)
w = d$x[2] - d$x[1]
s = cumsum( w*d$y ) # Probably better to use 'integrate' with 'approxfun'.
d$x[ which(s >= .2)[1] ]
But it's certainly not very 'defensible' (I won't defend it!),
and you would likely get a better (and defensible) answer with
quantile(x,.2)
Compare this with the 'real' value
qnorm(.2)
--
Karl Ove Hufthammer
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