Just a suggestion. It seems like each square can be denoted by x and y coordinates. Then you essentially have a two dimensional histogram/density that you need to plot. You can use the lattice functions "cloud"/"wireframe". You can also go for a heat map/contour plot, the lattice functions for that will be "levelplot"/"contourplot". In case the number of squares are small, you might prefer a two-dimensional histogram, "cloud" in lattice has an option to plot the point as histogram.
Ritwik. On 8/4/06, Gichangi, Anthony <[EMAIL PROTECTED]> wrote: > > Hi R users > > I have a dataset which represents points that are market by patients as > the > source of pain. > Basically the patients indicates by a cross on a chest pictures where > he/she > thinks is the > source of pain. The data was then digitalized by divinding the chest into > small squares and each > square was give value 1 if it was the center 2 if it was touched by the > markings and 3 if it was not > touched. I would like to plot this data on the chest like graph showing > the > intesities of different > points and later stratify the grouping variables to see the difference. > > Has anybody got an idea how I can go around this ? > > Help is highly appreciated. > > Regards > > Anthony Gichangi, M. sc. > Department of Statistics. > JB. Winsløvej 9B, > DK 5000 Odense C. > Tel: 00 45 6550 3379 > Mobile: 00 45 61105805 > > ______________________________________________ > [email protected] 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. > -- Ritwik Sinha Graduate Student Epidemiology and Biostatistics Case Western Reserve University http://darwin.cwru.edu/~rsinha [[alternative HTML version deleted]]
______________________________________________ [email protected] 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.
