R help - Aug 2012 - diagonal matrix, array attributes and how to keep from setting an attribute on "NULL"

Hello,

I've put the short version here and if anyone wants to run the code with
CollocInfer, I've given the full version in the file "analysis".

  I come at the question of array attributes and dimnames
 to try to simplify.

In a CollocInfer LS.profile analysis using this array 'Y' constructed
as follows:



w=rnorm(41,.05)
z=rnorm(41,.06)

yX<-cbind(w,z)
y<-as.array(yX)
colnames(y)=c("V","R")

	Y<-array(0,c(41,2,2))
 	Y[,1,]=y
 	Y[,2,]=y

	

 I receive an error

Error in as.array.default(Y) : attempt to set an attribute on NULL


So I think to name the attributes :

	varnames=c("V","R")

	rownames(Y)<-rownames(Y, do.NULL = FALSE, prefix = "Obs.")
	colnames(Y)[1:2]=c("one","two")

	assign("dimnames(Y)",list(rownames(Y),varnames,colnames(Y)))

 	Y2<-as.array(Y,dimnames=dimnames(Y))
 	assign("Y",Y2)

then rerun the analysis with the same result

Now traceback() gives:


7: as.array.default(Y)
6: as.array(Y)
5: kronecker(X, Y)
4: kronecker(X, Y)
3: diag(rep(1, nrep)) %x% basisvals$bvals.obs
2: LS.setup(pars, coefs, fn, basisvals, lambda, fd.obj, more, data,
       weights, times, quadrature, eps = 1e-06, posproc, poslik,
       discrete, names, sparse)
1: Profile.LS(fhn, data = data2, times = times, pars = pars, coefs = coefs,
       lambda = lambda, out.meth = "nls", control.in = control.in,
       control.out = control.out)

the first four numbers here(7..4) seem okay when I call each; but in number 3:
calling the given text produces the error:

	error in evaluating the argument 'X' in selecting a method for
function 'kronecker': Error in diag(rep(1, nrep)) :
  	error in evaluating the argument 'x' in selecting a method for
function 'diag': Error: object 'nrep' not found

At the outset in the manual, Hooker refers to the diagonal matrix,  it
seems without further explanation:

	In order to demonstrate replicated observations, we make use of another set of
	data generated at dierent initial conditions. We then need
concatenate these ob-
	servations in time, and create new values for bvals and weights. The function
	diag.block from the simex package is used below, but there are several packages
	in R that provide block-diagonal matrices.

I have a feeling this diagonal matrix is a component of R analysis
that, if corrected here,
could produce results, and I would be grateful if anyone who has
experience with its use
could offer some help.

A
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