I am exploring the result of clustering a large multivariate data set into a number of groups, represented, say, by a factor G.
I wrote a function to see how categorical variables vary between groups: > ddisp <- function(dvar) { + csqt <- chisq.test(G,dvar) + print(csqt$statistic) + print(csqt$observed) + print(round(csqt$expected)) + round(csqt$residuals) + } > > x <- ceiling(4*runif(100)) > G <- gl(4,1,100) > ddisp(x) X-squared 6.235645 dvar G 1 2 3 4 1 10 5 5 5 2 6 9 5 5 3 8 6 5 6 4 7 4 4 10 dvar G 1 2 3 4 1 8 6 5 6 2 8 6 5 6 3 8 6 5 6 4 8 6 5 6 dvar G 1 2 3 4 1 1 0 0 -1 2 -1 1 0 -1 3 0 0 0 0 4 0 -1 0 1 Warning message: Chi-squared approximation may be incorrect in: chisq.test(G, dvar) As I need to apply this function to a large number of variables x it would be helpful if the function printed "x" rather than the formal argument "dvar". I have a vague idea that things like deparse() and substitute() will come into the solution but I have not yet come up with the right incantation. Any help appreciated! Murray Jorgensen -- Dr Murray Jorgensen http://www.stats.waikato.ac.nz/Staff/maj.html Department of Statistics, University of Waikato, Hamilton, New Zealand Email: [EMAIL PROTECTED] Fax 7 838 4155 Phone +64 7 838 4773 wk Home +64 7 825 0441 Mobile 021 1395 862 ______________________________________________ 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 and provide commented, minimal, self-contained, reproducible code.