If v is your original data, v <- c(-20, rep(0,98), 20) why not use mean( -20 < v & v < 2) as your estimate of the probability that v is in (-20,2)?
Estimating a density is like taking the derivative of a smooth of the empirical distribution function, so why not eliminate the middleman instead of integrating the estimated density? Any difference between the two methods tells more about the smoothing used than about the data involved. (Not that I am any sort of expert in this matter.) Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf Of Greg Snow > Sent: Saturday, January 28, 2012 8:12 PM > To: Duke; r-help@r-project.org > Subject: Re: [R] percentage from density() > > If you use logspline estimation (logspline package) instead of kernel density > estimation then this is > simple as there are cumulative area functions for logspline fits. > > If you need to do this with kernel density estimates then you can just find > the area over your region > for the kernel centered at each data point and average those values together > to get the area under the > entire density estimate. > > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf Of Duke > Sent: Friday, January 27, 2012 3:45 PM > To: r-help@r-project.org > Subject: [R] percentage from density() > > Hi folks, > > I know that density function will give a estimated density for a give > dataset. Now from that I want to have a percentage estimation for a > certain range. For examle: > > > y = density(c(-20,rep(0,98),20)) > > plot(y, xlim=c(-4,4)) > > Now if I want to know the percentage of data lying in (-20,2). Basically > it should be the area of the curve from -20 to 2. Anybody knows a simple > function to do it? > > Thanks, > > D. > > ______________________________________________ > 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. ______________________________________________ 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.
