Hi, Jona. I had a very similar question recently, and got some excellent advice on this news group. See https://groups.google.com/d/msg/julia-users/--RaT-2QDSI/sOpsPEiQ4F4J
--Peter On Thursday, September 25, 2014 4:38:02 PM UTC-7, Jona Sassenhagen wrote: > > Hey, > in the context of linear regression/OLS, using Julia 0.4 on Mac OSX 10.9, > x\y > > returns > ERROR: argument matrix must be square > in lufact at linalg/umfpack.jl:110 > in factorize at linalg/cholmod.jl:1047 > > Indeed, x is a sparse, rectangular matrix, approx. 100000x1000. y is a > dense matrix of 100000x30, although I would be satisfied solving only one > line at a time. I have used similar (albeit larger and even sparser) data > in MATLAB and the solution is very fast, on the order of seconds. > > Can I use the backlash with sparse rectangular matrices? > > Also, the same x will probably be used in more equations in the future, > so I am considering storing a factorization. However, chol(x) very quickly > fills up all available memory (12GB). If it matters, x is highly collinear. > > (If it isn't obvious, I do not have much experience with linear algebra, > all of this is very new to me.) > Thanks, > Jona >
