If the x and y values are regularly spaced, you could use contour() or persp() to plot the densities. If they are not, you can use density(), loess(), gam(), kriging another function to estimate a smooth surface for the values and then estimate the values over a regular grid and then plot with contour, etc.
------------------------------------- David L Carlson Department of Anthropology Texas A&M University College Station, TX 77840-4352 -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Saptarshi Guha Sent: Monday, September 8, 2014 6:57 PM To: R-help@r-project.org Subject: [R] KDE routines for data that is aggregated Hello, Couldn't think of a better subject line. Rather than a matrix like x,y ..,.. .,.. I have a matrix like x,y,n, ..,..,.., ..,..,.. and so on. Also, sum(n) is roughly few hundred million. The number of rows is <1MM Are they routines to fit a 2d kde estimate to data provided in this form? I can sample from the data according to weights given by 'n' but i am curious if there is something that can use all the data when given a structure of this form. Regards Saptarshi [[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.
