I should have said that matrix inverse accepts most
"tall" matrices and most square matrices, and rejects 
"wide" matrices.  

The reason is that the argument matrix must be
non-singular, i.e. having linearly independent columns.
A matrix can have at most {:$y independent columns, 
so no wide matrix can qualify.  "Most" because most tall
and most square matrices are non-singular.



----- Original Message -----
From: Roger Hui <[email protected]>
Date: Tuesday, March 24, 2009 23:04
Subject: Re: [Jprogramming] QR Decomposition
To: Programming forum <[email protected]>

> The documentation does say that the argument y must be
> in the domain of matrix inverse (%.).  Matrix inverse
> accepts "tall" matrices and rejects "wide" matrices.
> (And of course accepts most square matrices.)
> 
> 
> 
> ----- Original Message -----
> From: "Leigh J. Halliwell" <[email protected]>
> Date: Monday, March 23, 2009 16:05
> Subject: [Jprogramming] QR Decomposition
> To: 'Programming forum' <[email protected]>
> 
> > Dear J Forum:
> >  
> > I've been experimenting with 128!:0 (QR matrix decomposition) 
> as 
> > follows: 
> > B =. |: A =.  ? 4 7 $10
> >    $ each B;A
> > ----T---┐
> > │7 4│4 7│
> > L---+----
> >    $ each 128!:0 A
> > |length error
> > |   $each     128!:0 A
> >    $ each 128!:0 B
> > ----T---┐
> > │7 4│4 4│
> > L---+----
> >    
> > This suggests that the row dimension of the argument must be 
> > greater than or
> > equal to the column dimension, and hence that T(Q) mmult Q is 
> > the identity
> > matrix (orthogonal/Hermetian).  If so, then noting this in 
> > the Vocabulary
> > would be helpful.
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