My R package, "probhat", provides plots of bivariate PDFs and bivariate
CDFs, using kernel smoothing.
Note that there is no bivariate quantile function, as such.
Here's the vignette:
https://cran.r-project.org/web/packages/probhat/vignettes/probhat.pdf
This contains examples.
Note that I'm not s
I think something like table(Preference, Sex, data=table) will get you
started. With 3+ variables, you are probably looking for a MCA analysis
or simple CA using the stacked approach.
Your SAS table statement,
table Preference, Sex Age Time;
treats Preference vs. all combinations of Sex, Age &
Hi Alfredo,
I have not used SAS nor done a correspondence analysis in many years
but to give R-help readers an idea of what you are doing, we probably
need a short statement of the substantive problem that would lead to
the SAS program:
proc corresp data=table dim=2 outc=_coord;
table Preferen
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