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2010 Jul 14
5
Matrix Size
hi -
i just started using R as i am trying to figure out how perform a linear
regression on a huge matrix.
i am sure this topic has passed through the email list before but could
not find anything in the archives.
i have a matrix that is 2,000,000 x 170,000 the values right now are
arbitray.
i try to allocate this on a x86_64 machine with 16G of ram and i get the
following:
> x <-
2004 May 02
0
parallel REML computation
...f the parallel
(restricted/residual) maximum (REML/ML) gradient algorithms from the paper:
J.M. Malard, "Parallel Restricted Maximum Likelihood Estimation
for Linear models with a Dense Exogenous Matrix", Parallel
Computing, 28, pp343-53, 2002.
The code has been upgraded to PETSc 2.2.0 and TAO 1.6 and is available
by sending an email at acre-developers at eml.pnl.gov. This software solves
covariance component estimation problems for linear models were the
residual vector comes from a normal distribution. The Cholesky
factorization of the covariance matrix is a sparse matrix...