To bootstrap from a histogram, use
sample(bins, replace = TRUE, prob = counts)
Note that a kernel density estimate is biased, so some bootstrap
confidence intervals have poor coverage properties.
Furthermore, if the kernel bandwidth is data-driven then the estimate
is not functional, so some
On Fri, Aug 31, 2012 at 12:15 PM, David L Carlson dcarl...@tamu.edu wrote:
Using a data.frame x with columns bins and counts:
x - structure(list(bins = c(3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5,
11.5, 12.5, 13.5, 14.5, 15.5), counts = c(1, 1, 2, 3, 6, 18,
19, 23, 8, 10, 6, 2, 1)),
Hello,
I wanted to know if there was way to convert a histogram of a data-set to a
kernel density estimate directly in R ?
Specifically, I have a histogram [bins, counts] of samples {X1 ...
XN} of a quantized variable X where there is one bin for each level of X,
and I'ld like to directly get a
University
College Station, TX 77843-4352
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of firdaus.janoos
Sent: Friday, August 31, 2012 9:52 AM
To: r-help@r-project.org
Subject: [R] Histogram to KDE
Hello,
I wanted to know
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