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From Kim van der Linde <...@kimvdlinde.com>
Subject Re: [MATH] Contributing
Date Tue, 10 Aug 2004 13:02:26 GMT
Hi Mark,

Logically, the modules have to fit in with the existing structure. I was 
anyway already planning to revise the MVE module and start to 
incorporate the commons-MATH package. I wil have a look at the extisting 
package and come back with classes that would fit in, or post the 
questions here when I can not figure it out.

Cheers,

Kim

Mark R. Diggory wrote:

> Hi Kim,
> 
> I think we have a bit of work to complete in extending the api into 
> areas of multivariate analysis/statistics and would be interested in 
> implementations in that area. I think the big thing is that we would 
> like to see implementation be based on the existing library architecture 
> as well, so goal might be to see if these could be easily modified to 
> work with the existing Matrix/Statistics classes in our api.
> 
> thanks,
> Mark
> 
> Kim van der Linde wrote:
> 
>> Hi Phil,
>>
>> Thanks for the answer, and I was talking about numerical stability.
>>
>> On an other track, if the math group is interested, I can provide some
>> classes for Multivariate Minimum Volume Ellipsoid outlier detection,
>> Covariances, common matrix types as SSCP, covariance and correlation,
>> multivariate euclidian and mahalanobis distances and maybe some other
>> classes as model 2 regressions (RMA: Reduced Major Axis). Interested?
>>
>> Kim
>>
>> Phil Steitz wrote:
>>
>>> Kim van der Linde wrote:
>>>
>>>> Hi All,
>>>>
>>>> I have a question. How stable are the matrix classes as implemented?
>>>>
>>>> Cheers,
>>>>
>>>> Kim
>>>>
>>>>
>>> Hi Kim,
>>>
>>> If your question is about the API, then the answer is that we are 
>>> planning no changes prior to the imminent 1.0 release.  If your 
>>> question is about numerical stability, performance or correctness 
>>> there are two things to say:
>>>
>>> 1) The javadoc describes the algorithms used to perform matrix 
>>> operations.  The algorithms are general purpose, so they will not 
>>> always give the best results (or performance) for all matrices. For 
>>> most practical problems, the implementations should work fine. Have a 
>>> look at the docs and consult a numerical linear algebra text (or a 
>>> numerical analyst) or ask more specific questions here if you want to 
>>> know about individual operations. Eventually, we will provide support 
>>> for a wider variety of algorithms.  For 1.0, what you see now is what 
>>> you get.
>>>
>>> 2) Our confidence in implementation correctness is based pretty much 
>>> entirely on the unit tests at this point. This is new code, not yet 
>>> released. We are in the process of cutting a release candidate 
>>> including these classes. User feedback and/or additional test cases 
>>> will be greatly appreciated.
>>>
>>> Phil
>>>
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>>
> 

-- 
http://www.kimvdlinde.com



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