- Referenced in 1499 articles
- solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue...
- Referenced in 554 articles
- method for the solution of nonlinear least squares problems. Both, overdetermined and underdetermined nonlinear least...
- Referenced in 461 articles
- solve linear equations and linear least-squares problems. The package solves linear systems whose matrices ... indefinite, symmetric positive definite, triangular, and tridiagonal square. In addition, the package computes ... rectangular matrices and applies them to least-squares problems. LINPACK uses column-oriented algorithms...
- Referenced in 376 articles
- solving systems of linear equations, least squares problems, and eigenvalue problems. The goals of both ... factorization, matrix inversion, full-rank linear least squares problems, orthogonal and generalized orthogonal factorizations, orthogonal...
- Referenced in 513 articles
- object, and finally performing verification through least-squares solution for consistent pose parameters. This approach...
- Referenced in 460 articles
- singular value decomposition to solve certain least-squares problems. EISPACK has been superseded...
- Referenced in 304 articles
- LSQR: Sparse Linear Equations and Least Squares Problems. An iterative method is given for solving...
- Referenced in 194 articles
- total least squares problem: computational aspects and analysis. Total least squares...
- Referenced in 246 articles
- quadratic programming, nonlinear optimization, and nonlinear least squares. You can use these solvers to find...
- Referenced in 123 articles
- norm solution of an underdetermined least-squares problem. Basis Pursuit DeNoise (BPDN) fits the least ... squares problem only approximately, and a single parameter determines a curve that traces ... optimal trade-off between the least-squares fit and the one-norm of the solution ... gradient-projection method approximately minimizes a least-squares problem with an explicit one-norm constraint...
- Referenced in 196 articles
- random number generators, special functions and least-squares fitting. There are over 1000 functions...
- Referenced in 107 articles
- Nonlinear Statistical Models”. The program computes least squares estimates for a univariate nonlinear regression model ... generalized least squares estimates for a multivariate nonlinear regression model. Use the SUR option ... implicit form, it computes three-stage least-squares estimates, TSLS option, and for nonlinear dynamic...
- Referenced in 143 articles
- analyzing power-law data, such as least-squares fitting, can produce substantially inaccurate estimates...
- Referenced in 122 articles
- software and services, from linear systems, least squares, and eigenvalue computations in a wide variety...
- Referenced in 89 articles
- When the problem is singular, a least-squares solution is computed. Singularities induced...
- Referenced in 87 articles
- including systems of linear equations, linear least squares problems, eigenvalue problems, and singular value problems...
- Referenced in 79 articles
- linear systems of equations and linear least squares problems, in particular for systems with multiple...
- Referenced in 79 articles
- point Jacobi, block Jacobi, Gauss-Seidel, least-squares polynomials, and overlapping domain decomposition using sparse...
- Referenced in 70 articles
- models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized...