You may want to look at the logspline package. It is another way of estimating densities and allows you to specify boundries on the domain of x.
-- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [EMAIL PROTECTED] (801) 408-8111 > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Rainer M Krug > Sent: Wednesday, January 16, 2008 2:35 AM > To: r-help > Subject: [R] Question concerning pdfs > > Hi > > I have a dataset of absolute growth rates g ranging from > close to 0 to around whatever of which I want to calculate a pdf. > If I use density(g) the pdf will extend to below 0 so I > logtransform g and do d <- density(log(g)). > Now I would like to transform this pdf back, i.e. d$x <- > exp(d$x) but what do I have to do with d$y? > > (below is a small example) > > Thanks for your help, > > Rainer > > > g <- exp(rnorm(100)) ## Just to generate the example data > > d <- density(log(g)) > dx <- d$x > dp <- d$y > > sum(c(0, (diff(dx))) * dp) ## this is equal to one plot(dx, dp) > > dx2 <- exp(dx) > dp2 <- ??????? ## what should I do here? > > plot(dx2, dp2) ## what should I do here? > sum(c(0, (diff(exp(dx2)))) * dp2) ## this should be one > > > sum( c(0, (diff(dx2))) * ( dp1 / c(1, (diff(exp(dx2)))) * c(0, > (diff(dx1)))) ) ##This is obviously also one, but can I > use this to define my dp2? i.e. > > dp2 <- dp1 / c(1, (diff(exp(dx2)))) * c(0, (diff(dx1)))) ###???? > > ______________________________________________ > 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.
