Thanks David for your response.I had done that. Problem is not with the computations, but in the interpretation. Assume that x ordinates are 'time' [1:3472], and y are associated parameter values. Now density gives me 512/1024/2048 x-ordinates, of which some (7 to be precise) are negative. What do I make of the non-zero probability at **negative** times?
If you see your rnorm case, you get the first few items negative. If the x items are bounded non-negative, what would density estimates at negative x-points mean? I can't do a linear scaling because that will disturb the density estimates on different days. Regards, pradeep On Wed, Mar 25, 2009 at 11:39 PM, David Winsemius <dwinsem...@comcast.net>wrote: > I am afraid your notion of a "concrete idea" is less concrete than what I > would need to understand what you are requesting. Your first lines of > example code should be: > > library(<if the density function is not from stats>) > <sample data construction of x> > density(x, <some set of parameters>) > > ... since stats::density() by default would return 512 y estimates, even > if the length of x were longer. > > > x <- rnorm(3471) > > plot(density(x)) > > str(density(x)) > List of 7 > $ x : num [1:512] -3.98 -3.96 -3.94 -3.93 -3.91 ... > $ y : num [1:512] 7.98e-06 > > -- > David Winsemius > > > On Mar 25, 2009, at 9:30 AM, Pradeep Raje wrote: > > Dear all:Request your indulgence. The econophysics gurus do this stuff all >> the time: all their PDFs are smooth, with neat log x axis. >> 1. The kernel density estimate (KDE) function returns the empirical >> probability density at 2^n points (min: 512). The big question is how do I >> scale back the x-values (say, density$x) to x-values in terms of the >> original dataset? >> 2. To give you a concrete idea, i have a dataset of 3471 obs (x=date >> index, >> y=parameter values). Now the density estimate d<-density(x) gives be 2048 >> x-values. When I plot the PDF, the x axis is obviously d$x, length=2048. >> 3. How can I scale back these 2048 values to get a sense of calendar time >> (original date index)? >> 4. Subsidiary question is: how do i bring in the remaining values >> (3471-2048)? >> > > You seem to have the idea that the original data is "lined up" with the > density estimates. That is not so. > > >> Thanks very much in advance. >> pradeep >> >> [[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. >> > > David Winsemius, MD > Heritage Laboratories > West Hartford, CT > > [[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.
