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Matrix Algebra support

 
 
Robert M. Gary
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      11-11-2005
I want to be able to multiply 2d integer arrays as well as invert them
for some matrix algebra calculations that my financial modeling
requires. I could write these routines myself but wondering if
something already exists out there. Are there any matrix algebra
packages available.

-Robert

 
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Jim Korman
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      11-11-2005
On 11 Nov 2005 14:27:10 -0800, "Robert M. Gary" <(E-Mail Removed)>
wrote:

>I want to be able to multiply 2d integer arrays as well as invert them
>for some matrix algebra calculations that my financial modeling
>requires. I could write these routines myself but wondering if
>something already exists out there. Are there any matrix algebra
>packages available.
>
>-Robert


Google is our friend.....

Second hit using {java matrix library}

http://math.nist.gov/javanumerics/jama/
 
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Robert M. Gary
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      11-11-2005
Cool. I was hoping to get some feedback on what people's experiences
were with different packages they may have used too.

-Robert

 
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Jim Korman
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      11-12-2005
On 11 Nov 2005 15:08:53 -0800, "Robert M. Gary" <(E-Mail Removed)>
wrote:

>Cool. I was hoping to get some feedback on what people's experiences
>were with different packages they may have used too.
>
>-Robert


Robert, Haven't tried this package yet! But it looks good.
Also note that this is NIST "product". Such things are usually
pretty good.

Jim
 
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Googmeister
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      11-12-2005

Jim Korman wrote:
> On 11 Nov 2005 15:08:53 -0800, "Robert M. Gary" <(E-Mail Removed)>
> wrote:
>
> >Cool. I was hoping to get some feedback on what people's experiences
> >were with different packages they may have used too.
> >
> >-Robert

>
> Robert, Haven't tried this package yet! But it looks good.
> Also note that this is NIST "product". Such things are usually
> pretty good.


Iv'e used the NIST/Mathworks product known as JAMA, and
was quite happy with it. It implements the de factor standard
numerical linear algebra algorithms from LINPACK and EISPACK.
JAMA is probably not as optimized (for speed) as its
FORTRAN and MATLAB competitors, but the code should
be rock solid.

 
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