
ScaLAPACK
 Referenced in 407 articles
[sw00830]
 matrix inversion, fullrank linear least squares problems, orthogonal and generalized orthogonal factorizations, orthogonal transformation...

LAPACK
 Referenced in 1647 articles
[sw00503]
 leastsquares solutions of linear systems of equations, eigenvalue problems, and singular value problems ... matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related...

LINPACK
 Referenced in 514 articles
[sw04209]
 linear leastsquares problems. The package solves linear systems whose matrices are general, banded, symmetric ... indefinite, symmetric positive definite, triangular, and tridiagonal square. In addition, the package computes ... rectangular matrices and applies them to leastsquares problems. LINPACK uses columnoriented algorithms...

NAPACK
 Referenced in 71 articles
[sw11666]
 optimization. It may be used to solve linear systems, to estimate the condition number ... invert a matrix, to solve least squares problems, to perform unconstrained minimization, to compute eigenvalues ... decomposition. The package has special routines for general, band, symmetric, indefinite, tridiagonal, upper Hessenberg...

Ceres Solver
 Referenced in 8 articles
[sw20619]
 solve Nonlinear Least Squares problems with bounds constraints and general unconstrained optimization problems...

nlr
 Referenced in 9 articles
[sw05244]
 quasilikelihood, generalized nonlinear least squares, and some robust fitting problems. The accompanying test examples ... include members of the generalized linear model family, extensions using nonlinear predictors (“nonlinear GLIM ... such as linearinparameter multinomial probit models. The basic method, a generalization ... NL2SOL algorithm for nonlinear least squares, employs a model/trustregion scheme for computing trial steps, exploits...

MINRESQLP
 Referenced in 20 articles
[sw11181]
 solving symmetric or Hermitian linear systems or leastsquares problems. If the system is singular ... also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes...

MINRES
 Referenced in 33 articles
[sw13371]
 conjugategradient type method for solving sparse linear equations: Solve ... really solving one of the leastsquares problems minimize ... leastsquares solution with small Ar (where r=b−Ax), but in general...

TENSOLVE
 Referenced in 28 articles
[sw00956]
 systems of nonlinear equations and nonlinear leastsquares problems using tensor methods. This article describes ... solving systems of nonlinear equations and nonlinear problems, using a new class of methods called ... intended for small to mediumsized problems, say with up to 100 equations and unknowns ... standard method based on a linear model. The tensor method approximates...

LSSVMlab
 Referenced in 26 articles
[sw07367]
 recent developments in kernel based methods in general. Originally, it has been introduced within ... solves convex optimization problems, typically quadratic programs. Least Squares Support Vector Machines ... standard SVMs which lead to solving linear KKT systems. LSSVMs are closely related...

QPOPT
 Referenced in 17 articles
[sw07859]
 QPOPT: Fortran package for constrained linear leastsquares and convex quadratic programming. QPOPT ... subroutines for minimizing a general quadratic function subject to linear constraints and simple upper ... linear programming and for finding a feasible point for a set of linear equalities ... QPOPT is not intended for large sparse problems, but there is no fixed limit...

ParaSails
 Referenced in 27 articles
[sw11521]
 with 216 million equations. ParaSails uses leastsquares (Frobenius norm) minimization to compute a sparse ... sequence of linear solves. ParaSails solves symmetric positive definite (SPD) problems using a factorized ... preconditioner. ParaSails can also solve general (nonsymmetric and/or indefinite) problems with a nonfactorized preconditioner...

BCSLIBEXT
 Referenced in 3 articles
[sw13150]
 linear equations, large sparse least squares problems, solution of large sparse real symmetric generalized eigenproblems ... core solution of large dense systems of linear equations, outofcore solution of real...

GELDA
 Referenced in 33 articles
[sw00331]
 example, in the solution of linear quadratic optimal control problems and differentialalgebraic Riccati equations ... many of the standard integration methods for general DAEs require the system to have differentiation ... properties can be treated in a least squares sense. In the case that...

sparseLM
 Referenced in 5 articles
[sw04810]
 cumulative geometric error using nonlinear leastsquares fitting. Typically, this error is characterized ... estimated, which leads to minimization problems possessing a sparse structure. Taking advantage of this sparseness ... sparsity pattern is problemdependent, its exploitation for a particular estimation problem requires nontrivial ... sparseLM, a generalpurpose software package for sparse nonlinear least squares that can exhibit...

SDLS
 Referenced in 8 articles
[sw04788]
 solve approximately convex conic leastsquares problems. Geometrically, these problems amount to finding the projection ... affine subspace. SDLS solves the dual problem with a quasiNewton minimization algorithm, using ... matrices, achieved by Matlab’s builtin linear algebra functions. Note that SDLS ... solving and experimenting with general conic leastsquares. Up to our knowledge, no such freeware...

dqed
 Referenced in 3 articles
[sw05224]
 presented for solving nonlinear least squares and nonlinear equation problems. The algorithm is based ... problem statement may include simple bounds or more general linear constraints on the unknowns ... computations for the modelproblem require a constrained nonlinear least squares solver. This is done...

TOMSYM
 Referenced in 3 articles
[sw06288]
 Optimizer. The environment is included with the general TOMLAB Base Module. The class allows ... problem types, including: Linear and quadratic programming Nonlinear and semidefinite programming Least squares problem...

g2o
 Referenced in 8 articles
[sw22795]
 general framework for graph optimization. g2o is an opensource C++ framework for optimizing graph ... wide range of problems and a new problem typically can be specified ... SLAM and BA. A wide range of problems in robotics as well as in computer ... source C++ framework for such nonlinear least squares problems. g2o has been designed...

NCL
 Referenced in 1 article
[sw36527]
 general smooth optimization problems where first and second derivatives are available, including problems whose constraints ... linearly independent at a solution (i.e., do not satisfy the LICQ). It is equivalent ... LICQ, and on nonlinear leastsquares problems and general problems from the CUTEst test...