On 6/9/06, Rafael A. Irizarry <ririzarr at jhsph.edu>
wrote:> Hi!
>
> I have used the Matrix package (Version: 0.995-10) successfully
> to obtain the OLS solution for a problem where the design matrix X is
> 44000x6000. X is very sparse (about 80000 non-zeros elements).
>
> Now I want to do WLS: (X'WX)^-1X'Wy
>
> I tried W=Diagonal(length(w),w) and
> wX=solve(X,W)
>
> but after various minutes R gives a not enough
> memory error (Im using a 64bit machine with 16Gigs of RAM).
That's an interesting question, Rafael, and very timely. I happen to
be visiting Martin Maechler this week and he mentioned to me just a
few minutes ago that we should add the capability for sparse least
squares calculations to the Matrix package.
Just for clarification, did you really mean wX = solve(X, W) above or
were you thinking of wX = crossprod(X, W)?
I would suggest storing the square root of the diagonal matrix W as a
sparse matrix
> w <- abs(rnorm(88000))
> ind <- seq(along = w) - 1:1
> W <- as(new("dgTMatrix", i = ind, j = ind, x = sqrt(w), Dim =
c(length(w), length(w))), "dgCMatrix")
> str(W)
Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
..@ i : int [1:88000] 0 1 2 3 4 5 6 7 8 9 ...
..@ p : int [1:88001] 0 1 2 3 4 5 6 7 8 9 ...
..@ Dim : int [1:2] 88000 88000
..@ Dimnames:List of 2
.. ..$ : NULL
.. ..$ : NULL
..@ x : num [1:88000] 0.712 0.989 1.032 0.348 0.573 ...
..@ factors : list()
(The 1:1 expression in the calculation of ind is a cheap trick to get
an integer value of 1 so that ind stays integer). Now you should be
able to create wX <- W %*% X and wy <- W %*% y very quickly.
> I ended up doing this:
> wX=Matrix(as.matrix(X)*sqrt(w),sparse=TRUE)
> coefs1=as.vector(solve(crossprod(wX),crossprod(X,w*y)))
>
> which takes about 1-2 minutes, but it seems a better way, using the
> diagonal matrix, should exist. If there is I'd appreciate hearing it.
If
> not, Im happy waiting 1-2 minute x #of iters.
>
>
> Thanks,
> Rafael
>
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