[R] matrix multivariate bootstrap: order of results in $t component

[Michael Friendly]

[This question is hopefully straight-forward, but difficult to provide 
reproducible code.]

I'm doing a multivariate bootstrap, using boot::boot(),
where the output of the basic computation is a k x p matrix of coefficients,
representing a tuning constant x variable, as shown in the $t0 component 
from my run, giving a 3 x 6 matrix

 > lboot$t0
          GNP Unemployed Armed.Forces Population  Year GNP.deflator
0.00 -3.4472     -1.828      -0.6962   -0.34420 8.432      0.15738
0.01 -0.1798     -1.361      -0.5881   -1.00317 5.656     -0.02612
0.08  1.0907     -1.086      -0.4583   -0.08596 2.642      0.57025
 >

?boot doesn't say how these are strung out to give the 1 x 18 vector in 
each row of lboot$t, but I believe
it is done columnwise -- is this correct?

That is, I think that the column names for  the bootstrap results,  
lboot$t, should vary most quickly down
the columns:

 > c(t(outer(colnames(lboot$t0), rownames(lboot$t0), paste, sep=':')))
  [1] "GNP:0.00"          "GNP:0.01"          "GNP:0.08"
  [4] "Unemployed:0.00"   "Unemployed:0.01"   "Unemployed:0.08"
  [7] "Armed.Forces:0.00" "Armed.Forces:0.01" "Armed.Forces:0.08"
[10] "Population:0.00"   "Population:0.01"   "Population:0.08"
[13] "Year:0.00"         "Year:0.01"         "Year:0.08"
[16] "GNP.deflator:0.00" "GNP.deflator:0.01" "GNP.deflator:0.08"
 >

So, the first bootstrap resample would correspond to

 > lboot$t[1,]
          GNP:0.00          GNP:0.01          GNP:0.08   Unemployed:0.00
          -10.1495           -0.8622            1.0566           -2.6131
   Unemployed:0.01   Unemployed:0.08 Armed.Forces:0.00 Armed.Forces:0.01
           -1.5316           -1.1988           -0.9279           -0.7141
Armed.Forces:0.08   Population:0.00   Population:0.01   Population:0.08
           -0.5748            1.8401           -0.9989           -0.3155
         Year:0.00         Year:0.01         Year:0.08 GNP.deflator:0.00
           12.8984            6.4378            2.7761            0.9417
GNP.deflator:0.01 GNP.deflator:0.08
            0.1871            0.9797

Or, as a matrix:

 > matrix(lboot$t[1,], nrow=3)
          [,1]   [,2]    [,3]    [,4]   [,5]   [,6]
[1,] -10.1495 -2.613 -0.9279  1.8401 12.898 0.9417
[2,]  -0.8622 -1.532 -0.7141 -0.9989  6.438 0.1871
[3,]   1.0566 -1.199 -0.5748 -0.3155  2.776 0.9797
 >

Finally, if the above is correct, how can I easily take my R=800 
bootstrap estimates in
the 800 x 18 matrix lboot$t and restructure them in a (2400=800x3) x 6 
matrix or data.frame
corresponding to stacking the matrices like the above for each bootstrap 
sample?

thanks,
-Michael

-- 
Michael Friendly     Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University      Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street    Web:   http://www.datavis.ca
Toronto, ONT  M3J 1P3 CANADA