English-Russian Dictionary on Probability, Statistics, and Combinatorics. — Philadelphia and Moscow. Society for Industrial and Applied Mathematics and TVP Science Publishers. K. A. Borovkov. 1994.
Least 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… … Wikipedia
Linear 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 … Wikipedia
Ordinary 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… … Wikipedia
Total 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… … Wikipedia
Generalized 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 … Wikipedia
Lack-of-fit sum of squares — In statistics, a sum of squares due to lack of fit, or more tersely a lack of fit sum of squares, is one of the components of a partition of the sum of squares in an analysis of variance, used in the numerator in an F test of the null hypothesis… … Wikipedia
Generalized 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… … Wikipedia
Newton's method — In numerical analysis, Newton s method (also known as the Newton–Raphson method), named after Isaac Newton and Joseph Raphson, is a method for finding successively better approximations to the roots (or zeroes) of a real valued function. The… … Wikipedia
Non-negative matrix factorization — NMF redirects here. For the bridge convention, see new minor forcing. Non negative matrix factorization (NMF) is a group of algorithms in multivariate analysis and linear algebra where a matrix, , is factorized into (usually) two matrices, and… … Wikipedia
Dynamic programming — For the programming paradigm, see Dynamic programming language. In mathematics and computer science, dynamic programming is a method for solving complex problems by breaking them down into simpler subproblems. It is applicable to problems… … Wikipedia
Curve fitting — best fit redirects here. For placing ( fitting ) variable sized objects in storage, see fragmentation (computer). Curve fitting is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points,… … Wikipedia
