Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems...
34 KB (5,382 words) - 19:37, 18 February 2024
Non-linear least squares is the form of least squares analysis used to fit a set of m observations with a model that is non-linear in n unknown parameters...
28 KB (4,538 words) - 09:54, 25 April 2024
of that for least squares. Least squares problems fall into two categories: linear or ordinary least squares and nonlinear least squares, depending on...
38 KB (5,492 words) - 02:45, 13 May 2024
Weighted least squares (WLS), also known as weighted linear regression, is a generalization of ordinary least squares and linear regression in which knowledge...
13 KB (2,232 words) - 05:28, 14 June 2023
methods for linear least squares entails the numerical analysis of linear least squares problems. A general approach to the least squares problem m i...
10 KB (1,526 words) - 10:20, 1 December 2022
statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression model (with...
64 KB (8,935 words) - 03:26, 16 May 2024
In constrained least squares one solves a linear least squares problem with an additional constraint on the solution. This means, the unconstrained equation...
5 KB (645 words) - 22:42, 28 January 2023
orthogonal regression, and can be applied to both linear and non-linear models. The total least squares approximation of the data is generically equivalent...
20 KB (3,293 words) - 00:07, 21 March 2024
The method of iteratively reweighted least squares (IRLS) is used to solve certain optimization problems with objective functions of the form of a p-norm:...
6 KB (834 words) - 07:02, 15 May 2024
Partial least squares regression (PLS regression) is a statistical method that bears some relation to principal components regression; instead of finding...
23 KB (2,928 words) - 06:06, 19 April 2024
; Hanson, Richard J. (1995). "23. Linear Least Squares with Linear Inequality Constraints". Solving Least Squares Problems. SIAM. p. 161. doi:10.1137/1...
8 KB (880 words) - 06:30, 26 August 2023
Nonlinear regression (redirect from Non-linear regression)
global minimum of a sum of squares. For details concerning nonlinear data modeling see least squares and non-linear least squares. The assumption underlying...
10 KB (1,394 words) - 02:15, 28 March 2024
In statistics, generalized least squares (GLS) is a method used to estimate the unknown parameters in a linear regression model. It is used when there...
18 KB (2,833 words) - 11:58, 1 May 2024
Conversely, the least squares approach can be used to fit models that are not linear models. Thus, although the terms "least squares" and "linear model" are...
70 KB (9,686 words) - 05:47, 13 May 2024
Coefficient of determination (redirect from Coefficient of determination in a multiple linear model)
In some cases, as in simple linear regression, the total sum of squares equals the sum of the two other sums of squares defined above: S S res + S S...
45 KB (6,208 words) - 21:35, 19 April 2024
Levenberg–Marquardt algorithm (redirect from Levenberg-Marquardt nonlinear least squares fitting algorithm)
damped least-squares (DLS) method, is used to solve non-linear least squares problems. These minimization problems arise especially in least squares curve...
22 KB (3,211 words) - 07:50, 26 April 2024
LOESS and LOWESS thus build on "classical" methods, such as linear and nonlinear least squares regression. They address situations in which the classical...
18 KB (2,557 words) - 14:15, 17 January 2024
Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function...
21 KB (2,407 words) - 17:40, 27 April 2024
Piecewise linear function Linear approximation Linear interpolation Discontinuous linear map Linear least squares "The term linear function means a linear form...
5 KB (651 words) - 01:03, 27 March 2024
the many linear programming techniques (including the simplex method as well as others) can be applied. Iteratively re-weighted least squares Wesolowsky's...
16 KB (2,150 words) - 01:48, 29 November 2023
common linear algebraic problems like solving linear systems of equations, locating eigenvalues, or least squares optimisation. Numerical linear algebra's...
18 KB (2,507 words) - 03:52, 21 December 2023
has simple closed forms, and can be parameterized with data using linear least squares. The Marchenko–Pastur distribution is important in the theory of...
22 KB (2,609 words) - 12:49, 10 February 2024
Gauss–Markov theorem (redirect from Gauss-Markow least squares theorem)
ordinary least squares (OLS) estimator has the lowest sampling variance within the class of linear unbiased estimators, if the errors in the linear regression...
28 KB (4,798 words) - 02:35, 13 March 2024
(X). Regression analysis Linear regression Least squares Linear least squares (mathematics) Non-linear least squares Least absolute deviations Curve...
5 KB (327 words) - 12:15, 30 October 2023
identified cluster is then subject to a verification procedure in which a linear least squares solution is performed for the parameters of the affine transformation...
68 KB (9,143 words) - 06:43, 11 January 2024
Least-squares adjustment is a model for the solution of an overdetermined system of equations based on the principle of least squares of observation residuals...
11 KB (1,397 words) - 20:12, 1 October 2023
method for training artificial neural networks. The simple example of linear least squares is used to explain a variety of ideas in online learning. The ideas...
25 KB (4,740 words) - 03:53, 2 May 2024
Projection matrix (section Ordinary least squares)
{A} ^{\textsf {T}}} . Suppose that we wish to estimate a linear model using linear least squares. The model can be written as y = X β + ε , {\displaystyle...
13 KB (1,918 words) - 11:20, 6 May 2024
number of variables in the linear system exceeds the number of observations. In such settings, the ordinary least-squares problem is ill-posed and is...
23 KB (4,270 words) - 23:10, 1 May 2024
transformation Least squares, linear least squares Gram–Schmidt process Woodbury matrix identity Vector space Linear combination Linear span Linear independence...
5 KB (377 words) - 12:12, 30 October 2023