• ScaLAPACK

  • Referenced in 421 articles [sw00830]
  • least squares problems, orthogonal and generalized orthogonal factorizations, orthogonal transformation routines, reductions to upper Hessenberg...
  • ARPACK

  • Referenced in 848 articles [sw04218]
  • problems. For many standard problems, a matrix factorization is not required. Only the action ... eigen-space is computed which is numerically orthogonal to working precision. Numerically accurate eigenvectors...
  • CIMGS

  • Referenced in 12 articles [sw17583]
  • CIMGS: An incomplete orthogonal factorization preconditioner. A new preconditioner for symmetric positive definite systems ... CIMGS), is based on an incomplete orthogonal factorization. CIMGS is robust both theoretically and empirically...
  • SOFAR

  • Referenced in 7 articles [sw31665]
  • sparse latent factors ranked by importance. Yet sparsity and orthogonality have been two largely incompatible ... suggest the method of sparse orthogonal factor regression (SOFAR) via the sparse singular value decomposition ... with orthogonality constrained optimization to learn the underlying association networks, with broad applications to both ... value decomposition, sparse principal component analysis, sparse factor analysis, and spare vector autoregression analysis. Exploiting...
  • MIQR

  • Referenced in 11 articles [sw07242]
  • problems. The algorithm builds the factorization by exploiting structural orthogonality in general sparse matrices ... patterns. The other columns are then block orthogonalized against columns of the independent ... with a standard QR or incomplete QR factorization. Dropping strategies are employed throughout the levels...
  • MPSolve

  • Referenced in 14 articles [sw05298]
  • factorizations, spectral factorizations, matrix polynomials and matrix power series, interpolation problems, orthogonal polynomials and rational...
  • rrpack

  • Referenced in 1 article [sw40512]
  • /j.1467-9868.2011.01002.x> and sparse and orthogonal factor regression (SOFAR) proposed by Uematsu...
  • TKPSVD

  • Referenced in 12 articles [sw28028]
  • Kronecker product to tensors such that each factor A(i)j in the TKPSVD ... tensor, after which a polyadic decomposition with orthogonal rank-1 terms is computed. We prove ... many different structured tensors, the Kronecker product factors...
  • ATC

  • Referenced in 1 article [sw39352]
  • approach is proposed to compress the orthogonal Tucker factors. Certain key improvements to the quantization...
  • AS 224

  • Referenced in 1 article [sw14095]
  • form a design with several orthogonal blocking factors (Algorithm...
  • GQLOG

  • Referenced in 8 articles [sw41348]
  • orthogonal with respect to weight functions of Laguerre and Jacobi type containing logarithmic factors...
  • FACTORIZE

  • Referenced in 5 articles [sw10039]
  • best factorization method (LU, Cholesky, LDL T , QR, or a complete orthogonal decomposition for rank ... does the right thing by factorizing A and solving the corresponding triangular systems...
  • PROC ANOVA

  • Referenced in 1 article [sw12083]
  • have designs in which the factors are all orthogonal to each other...
  • POET

  • Referenced in 1 article [sw20877]
  • covariance matrices in approximate factor models by thresholding principal orthogonal complements...
  • cheney-kincaid

  • Referenced in 25 articles [sw11656]
  • quadrature, adaptive Simpson’s integration, and discrete orthogonal polynomials, have been added. Many problem sets ... emphasis. More material on the LU factorization has been added in the chapter on solving...
  • v53i10.sas

  • Referenced in 1 article [sw24527]
  • Factorial Designs Generation: A SAS-Based Algorithm. Orthogonal fractional factorial designs (OFFDs) are frequently used ... number of levels of each factor nor on the orthogonality constraints. The algorithm is based...
  • CHFACT

  • Referenced in 5 articles [sw30976]
  • Implementing Cholesky factorization for interior point methods of linear programming. Every iteration of an interior ... linear programming requires computing at least one orthogonal projection of the objective function gradient onto ... problem constraint matrix A. The orthogonal projection itself is in turn dominated by the inversion ... specific issues of implementation of the Cholesky factorization that can be applied for solving such...
  • factor.switching

  • Referenced in 2 articles [sw33922]
  • issue in factor analytic models is the invariance with respect to orthogonal transformations. This problem ... Ntzoufras (2020) ) into raw MCMC samples of factor loadings, which are provided by the user...
  • qr_mumps

  • Referenced in 4 articles [sw38946]
  • method based on the QR or Cholesky factorization of the input matrix. Therefore ... stability provided by the use of orthogonal transformations comes at the cost of a higher ... solvers based on, e.g., the LU factorization such as MUMPS. qr_mumps supports real...
  • CholQR

  • Referenced in 12 articles [sw13049]
  • Mixed-precision Cholesky QR factorization and its case studies on multicore CPU with multiple gpus ... kernels. As a result, compared to other orthogonalization algorithms, CholQR obtains superior performance on many...