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 × Σ × V<sup>T</sup>. Let A be a m × n matrix, then U is a m × p orthogonal matrix, Σ is a p × p diagonal matrix with positive or null elements, V is a p × n orthogonal matrix (hence V<sup>T</sup> is also orthogonal) where p=min(m,n). Dim. ---------------------------------------------------------------------------- Dimitri Pourbaix * Institut d'Astronomie et d'Astrophysique * Don't worry, be happy CP 226, office 2.N4.211, building NO * and CARPE DIEM. Universite Libre de Bruxelles * Boulevard du Triomphe * Tel : +32-2-650.35.71 B-1050 Bruxelles * Fax : +32-2-650.42.26 http://sb9.astro.ulb.ac.be/~pourbaix * mailto:pourb...@astro.ulb.ac.be --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
