The methods I suggested work for square and non-square 
(tall, not wide) matrices.

   lii=: 1:@%. ::0:
   lii p: i.5 3
1
   lii p: i.3 5
0
   lii  i.5 3
0
   lii i.3 5
0

I agree that SVP is the way to go if numerical stability
is a concern.



----- Original Message -----
From: John Randall <[EMAIL PROTECTED]>
Date: Friday, September 7, 2007 9:05
Subject: Re: [Jgeneral] linear independence?
To: General forum <[email protected]>

> Roger Hui wrote:
> > To work with rows rather than columns, transpose
> > the matrix, and then:
> >
> > Method 0: the columns are linearly independent if
> > the matrix is invertible.
> >
> > lii=: 1:@%. ::0:
> >
> > Method 1: the columns are linearly independent
> > if the determinant is non-zero:
> >
> > lid=: 0: ~: [: -/ .* (|: +/ .* ])^:(>/@$)
> 
> I agree that this is the best way to go with square 
> matrices.  The rref
> method I suggested (which mimics pencil and paper methods) is a 
> good start
> for nonsquare matrices.  It can probably done better than 
> my suggested
> code.
> 
> However, the question of finding the rank of a matrix is difficult
> numerically.  The method usually suggested is singular value
> decomposition, but there has been a lot of work on methods for special
> matrices. See, for example
> 
> <http://www.neiu.edu/~zzeng/Papers/rankrev.pdf>
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