[R] SparseM and Stepwise Problem
roger at ysidro.econ.uiuc.edu
Wed Jan 31 03:05:34 CET 2007
One simple possibility -- if you can generate the X matrix in dense
X <- as.matrix.csr(X)
Unfortunately, there is no current way to go from a formula to a
matrix without passing through a dense version of X first.
need to use new() to define the X matrix directly. This is usually
difficult, but it depends on the model....
url: www.econ.uiuc.edu/~roger Roger Koenker
email rkoenker at uiuc.edu Department of Economics
vox: 217-333-4558 University of Illinois
fax: 217-244-6678 Champaign, IL 61820
On Jan 30, 2007, at 5:31 PM, davidkat at davidkatzconsulting.com wrote:
> I'm trying to use stepAIC on sparse matrices, and I need some help.
> The documentation for slm.fit suggests:
> slm.fit and slm.wfit call slm.fit.csr to do Cholesky decomposition
> and then
> backsolve to obtain the least squares estimated coefficients. These
> functions can be
> called directly if the user is willing to specify the design matrix
> in matrix.csr form.
> This is often advantageous in large problems to reduce memory
> I need some help or a reference that will show how to create the
> design matrix from
> data in matrix.csr form.
> Thanks for any help.
> David Katz
> 541 482-1137
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