From: Gabor Grothendieck <ggrothendieck_at_myway.com>

Date: Tue 22 Mar 2005 - 02:42:56 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue Mar 22 03:09:57 2005

Date: Tue 22 Mar 2005 - 02:42:56 EST

Witold Eryk Wolski <W.E.Wolski <at> ncl.ac.uk> writes:

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: Dear Rgurus,

*:
**: To my knowledge the best way to visualize the distribution of a discrete
**: variable X is
**: plot(table(X))
**:
**: The problem which I have is the following. I have to discrete variables
**: X and Y which distribution I would like to compare. To overlay the
**: distribution of Y with lines(table(Y)) gives not satisfying results.
**: This is the same in case of using density or histogram.
**:
**: Hence, I am wondering if there is a equivalent of the vioplot function
**: (package vioplot) for discrete variables
**: which starts with a boxplot and than adds a rotated plot(table()) plot
**: to each side of the box plot.
**:
**: Maybee I should ask it first: Does such a plot make any sense? If not
**: are there better solutions?
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You could try a barplot or a balloonplot:

tab <- table(stack(list(x1 = x1, x2 = x2))) # x1, x2 from Andy's post barplot(t(tab), beside = TRUE)

library(gplots)

balloonplot(tab)

Although intended for comparing data to a theoretical distribution, rootogram can compare two discrete distributions:

library(vcd)

rootogram(tab[,1], tab[,2])

Another possibility is to fit each distribution to a parametric form using vcd::distplot as shown in the examples on its help page.

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue Mar 22 03:09:57 2005

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