aggregate vs tapply; is there a middle ground?

Joseph -
   I'm sure there are clearer and more efficient ways to do it, but 
here's something
that seems to do what you want:

z = tapply(y,list(var1,var2,var3,var4),sum)
data.frame(do.call('expand.grid',dimnames(z)),y=do.call('rbind',as.list(z))) 


                                       - Phil Spector
                     Statistical Computing Facility
                     Department of Statistics
                     UC Berkeley
                     spector at stat.berkeley.edu


On Sat, 11 Feb 2006, Joseph LeBouton wrote:

Dear all,

I'm wanting to do a series of comparisons among 4 categorical variables:

a <- aggregate(y, list(var1, var2, var3, var4), sum)

This gets me a very nice 2-dimensional data frame with one column per
variable, BUT, as help for aggregate says, <<empty subsets are
removed>>.  I don't see in help(aggregate) how I can change this.

In contrast,
a <- tapply(y, list(var1, var2, var3, var4), sum)

gives me results for everything including empty subsets, but in an
awkward 4-dimensional array that takes me another 10 lines of
inefficient code to turn into a 2D data.frame.

Is there a way to directly do this calculation INCLUDING results for
empty subsets, and still obtain a 2D array, matrix, or data.frame?  OR
alternatively is there a simple way to mush the 4D result from the
tapply into a 2D matrix/data.frame?

thanks very much in advance for any help!

-jlb

-- 
************************************
Joseph P. LeBouton
Forest Ecology PhD Candidate
Department of Forestry
Michigan State University
East Lansing, Michigan 48824

Office phone: 517-355-7744
email: lebouton at msu.edu