generalized least squares method
1Generalized Gauss–Newton method — The generalized Gauss–Newton method is a generalization of the least squares method originally described by Carl Friedrich Gauss and of Newton s method due to Isaac Newton to the case of constrained nonlinear least squares problems …
2Least squares inference in phylogeny — generates a phylogenetic tree based on anobserved matrix of pairwise genetic distances andoptionally a weightmatrix. The goal is to find a tree which satisfies the distance constraints asbest as possible.Ordinary and weighted least squaresThe… …
3Least squares — The method of least squares is a standard approach to the approximate solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of… …
4Generalized minimal residual method — In mathematics, the generalized minimal residual method (usually abbreviated GMRES) is an iterative method for the numerical solution of a system of linear equations. The method approximates the solution by the vector in a Krylov subspace with… …
5least squares approximation — ▪ statistics in statistics, a method for estimating the true value of some quantity based on a consideration of errors (error) in observations or measurements. In particular, the line (function) that minimizes the sum of the squared… …
6Ordinary least squares — This article is about the statistical properties of unweighted linear regression analysis. For more general regression analysis, see regression analysis. For linear regression on a single variable, see simple linear regression. For the… …
7Non-linear least squares — is the form of least squares analysis which is used to fit a set of m observations with a model that is non linear in n unknown parameters (m > n). It is used in some forms of non linear regression. The basis of the method is to… …
8Linear least squares (mathematics) — This article is about the mathematics that underlie curve fitting using linear least squares. For statistical regression analysis using least squares, see linear regression. For linear regression on a single variable, see simple linear regression …
9Total least squares — The bivariate (Deming regression) case of Total Least Squares. The red lines show the error in both x and y. This is different from the traditional least squares method which measures error parallel to the y axis. The case shown, with deviations… …
10Iteratively re-weighted least squares — The method of iteratively re weighted least squares (IRLS) is a numerical algorithm for minimizing any specified objective function using a standard weighted least squares method such as Gaussian elimination. Whereas techniques are widely… …
