Dimitri Pourbaix a écrit :
> Bruce,
> 
>>
>> The 2.1 API docs for the Singular Value Decomposition say:
>>
>> The size p depends on the chosen algorithm:
>>
>> for full SVD, p is n,
>> for compact SVD, p is the rank r of the matrix (i. e. the number of
>> positive singular values),
>> for truncated SVD p is min(r, t) where t is user-specified.
>>
>>
>> but I don't see any method or constructor to specify whether to do the
>> full, compact or truncated SVD.  Am I missing something, or is the code
>> missing something?
> 
> The doc is not synchronized with the source, I apologize (but the
> javadoc should be).  The code offers only one version which is none of
> the above!  From the Java file:
> 
>  The Singular Value Decomposition of matrix A is a set of three
>  matrices: U, Σ and V such that
>  A = U &times; &Sigma; &times; V<sup>T</sup>. Let A be  a m &times; n
>  matrix, then U is a m &times; p orthogonal matrix, &Sigma; is a
>  p &times; p diagonal matrix with positive or null elements, V is a
>  p &times; n orthogonal matrix (hence V<sup>T</sup> is also orthogonal)
>  where p=min(m,n).

This documentation bug is now fixed in subversion (changed javadoc of
the interface to match javadoc of the implementation).

Luc

> 
> Dim.
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> Dimitri Pourbaix                         *
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