[R] Unexp. behavior from boot with multiple statistics

[algorimancer]

I am attempting to use package boot to summarize and compare the performance
of three models.  I'm using R 2.13.0 in a Win32 environment.

My statistic function returns a vector of 6 values, 3 of which are error
rates for different models, and 3 are pairwise differences between those
error rates.  It looks like:

multiEst<-function(dat,i)
{
       ....
	c(E1,E2,E3,E2-E1,E3-E1,E3-E2);
}

then I call boot (using R=4 for simplicity of description) with:

multiBoot=boot(data,multiEst,R=4)

which gives reasonable results:

Bootstrap Statistics :
    original  bias    std. error
t1*     0.07  0.3775  0.04193249
t2*     0.08  0.3750  0.04654747
t3*     0.04  0.4200  0.05354126
t4*     0.01 -0.0025  0.00500000
t5*    -0.03  0.0425  0.01500000
t6*    -0.04  0.0450  0.01290994

and the resulting "t0" contains the expected estimates of the statistics,
> multiBoot$t0
[1]  0.07  0.08  0.04  0.01 -0.03 -0.04

however "t", which is supposed to contain bootstrap replicates of the
statistic, doesn't.  It looks like this:
> multiBoot$t
     [,1] [,2] [,3] [,4] [,5]  [,6]
[1,] 0.46 0.47 0.46 0.01 0.00 -0.01
[2,] 0.39 0.39 0.39 0.00 0.00  0.00
[3,] 0.45 0.46 0.47 0.01 0.02  0.01
[4,] 0.49 0.50 0.52 0.01 0.03  0.02

It is not clear where these columns come from --- they clearly do not
resemble the estimates in "t0".

If I define a separate statistic function for each desired estimate, the
resulting "t" and "t0" are as expected, however it is important in this case
that the separate estimates derive from the same bootstrap replicates.

Any helpful suggestions? Or have I come upon a bug in the implementation?

Note: the documentation provides the following definitions for these
returned variables:

t0 	The observed value of statistic applied to data.
t 	A matrix with R rows each of which is a bootstrap replicate of statistic. 









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