Thanks for these suggestions, Professor Ripley. It's interesting that
the function parameters in R are not truly dummy as they can effect
the result of a function.
Murray
Prof Brian Ripley wrote:
ddisp - function(dvar) {
yn - substitute(dvar)
csqt - eval.parent(substitute(chisq.test(G,dvar), list(dvar=yn)))
}
There are other ways, such as forming the cross-classification table,
setting its dimnames and passing that to chisq.test.
On Mon, 13 Nov 2006, Murray Jorgensen wrote:
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
G1 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
G1 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 wkHome +64 7 825 0441Mobile 021 1395 862
--
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 wkHome +64 7 825 0441Mobile 021 1395 862
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