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)), .Names = c("bins", "counts"), row.names = 4:16, class = "data.frame")
This will give you a plot of the kde estimate: xkde <- density(rep(bins, counts), bw="SJ") plot(xkde) As for the standard error or the confidence interval, you would probably need to use bootstrapping. ---------------------------------------------- David L Carlson Associate Professor of Anthropology Texas A&M 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 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 kde estimate of the pdf of X from the > histogram. Therefore, there is no additional quantization of X in the > histogram. Most KDE methods in R seem to require the original sample > set - and I would like to avoid re-creating the samples from the > histogram. Is there some quick way of doing this using one of the > standard > kde methods in R ? > > Also, a general statistical question - is there some measure of the > standard error or confidence interval or similar of a KDE of a data-set > ? > > Thanks, > -fj > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@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. ______________________________________________ R-help@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.