• Algorithm 971

  • Referenced in 8 articles [sw22686]
  • analysis and the calculation of truncated singular value decompositions. The present article presents an essentially ... superior for calculating the least singular values and corresponding singular vectors (or singular subspaces...
  • FaIMS

  • Referenced in 5 articles [sw06425]
  • algorithm to compute an approximate singular value decomposition (SVD) of least-squares operators related ... medium perturbation, a dense singular value decomposition of the Born operator requires...
  • Newmat

  • Referenced in 4 articles [sw05368]
  • submatrix, determinant, Cholesky decomposition, QR triangularisation, singular value decomposition, eigenvalues of a symmetric matrix, sorting...
  • ID

  • Referenced in 4 articles [sw14543]
  • forms of interpolative decompositions (IDs) and singular value decompositions (SVDs). The routines use algorithms based...
  • SOFAR

  • Referenced in 3 articles [sw31665]
  • factor regression (SOFAR) via the sparse singular value decomposition with orthogonality constrained optimization to learn ... tasks, such as biclustering with sparse singular value decomposition, sparse principal component analysis, sparse factor...
  • lsa

  • Referenced in 4 articles [sw19469]
  • derived statistically via a truncated singular value decomposition (a two-mode factor analysis) over...
  • DIFFRAC

  • Referenced in 4 articles [sw23902]
  • through a sequence of lower dimensional singular value decompositions. This framework has several attractive properties...
  • SVDComplexes

  • Referenced in 2 articles [sw27129]
  • implements the algorithms in the paper ”Singular value decomposition of complexes”, by D. Brake ... Stillman, https://arxiv.org/abs/1804.09838. Singular value decompositions of matrices are extremely useful in practice ... paper, we extend the notion of singular value decomposition from matrices over the reals...
  • ExPosition

  • Referenced in 2 articles [sw22023]
  • package ExPosition: Exploratory analysis with the singular value decomposition. ExPosition is for descriptive (i.e., fixed ... effects) multivariate analysis with the singular value decomposition...
  • randUTV

  • Referenced in 3 articles [sw30518]
  • alternative to algorithms for computing the Singular Value Decomposition (SVD). randUTV provides accuracy very close ... produces highly accurate approximations to the singular values of A. Unlike the SVD, the randomized...
  • DGELSS

  • Referenced in 3 articles [sw05210]
  • norm(| b - A*x |). using the singular value decomposition ... determined by treating as zero those singular values which are less than RCOND times...
  • SAM II

  • Referenced in 3 articles [sw14062]
  • eigenvalue problems by using generalized singular value decomposition. In this program there are three steps...
  • PyClimate

  • Referenced in 3 articles [sw29475]
  • Monte Carlo techniques). Other functions perform singular value decomposition of covariance matrices and canonical correlation...
  • Biplot

  • Referenced in 1 article [sw26237]
  • Biplot and Singular Value Decomposition Macros for Excel. The biplot display is a graph ... markers are calculated from the singular value decomposition of the data matrix. The biplot display ... data prior to the singular value decomposition and scaling of the markers following the decomposition...
  • ZKCM

  • Referenced in 2 articles [sw16659]
  • decomposition, the Hermitian-matrix diagonalization, the singular-value decomposition, and the discrete Fourier transform...
  • SVDLIBC

  • Referenced in 2 articles [sw14330]
  • file type conversions, along with computing singular value decompositions. Currently the only SVDPACKC algorithm implemented ... drawback that the low order singular values may be relatively imprecise, but that...
  • Algorithm 977

  • Referenced in 2 articles [sw25562]
  • software for computing the singular value decomposition (SVD) of real or complex matrices is proposed...
  • Apophenia

  • Referenced in 2 articles [sw05712]
  • package (such as OLS, probit, or singular value decomposition) but doesn’t tie the user...
  • RankRev

  • Referenced in 2 articles [sw22939]
  • much more efficient than the singular value decomposition when the matrix is of low rank...
  • SmallK

  • Referenced in 2 articles [sw21816]
  • been as significant as the singular value decomposition (SVD). However, due to nonnegativity constraints...