- least-squares reduction
- Метрология: приведение (данных) с помощью метода наименьших квадратов
Универсальный англо-русский словарь. Академик.ру. 2011.
Универсальный англо-русский словарь. Академик.ру. 2011.
Least-squares spectral analysis — (LSSA) is a method of estimating a frequency spectrum, based on a least squares fit of sinusoids to data samples, similar to Fourier analysis. [cite book | title = Variable Stars As Essential Astrophysical Tools | author = Cafer Ibanoglu |… … Wikipedia
Non-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… … 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
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
Linear least squares — is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to measurements obtained from experiments. The goals of linear least squares are to extract predictions from the… … Wikipedia
Non-linear iterative partial least squares — In statistics, non linear iterative partial least squares (NIPALS) is an algorithm for computing the first few components in a principal component or partial least squares analysis. For very high dimensional datasets, such as those generated in… … Wikipedia
Nonlinear dimensionality reduction — High dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lies on an embedded non linear manifold within… … Wikipedia
Dimension reduction — For dimensional reduction in physics, see Dimensional reduction. In machine learning, dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and feature… … Wikipedia
List of statistics topics — Please add any Wikipedia articles related to statistics that are not already on this list.The Related changes link in the margin of this page (below search) leads to a list of the most recent changes to the articles listed below. To see the most… … Wikipedia
mathematics — /math euh mat iks/, n. 1. (used with a sing. v.) the systematic treatment of magnitude, relationships between figures and forms, and relations between quantities expressed symbolically. 2. (used with a sing. or pl. v.) mathematical procedures,… … Universalium
Levenberg–Marquardt algorithm — In mathematics and computing, the Levenberg–Marquardt algorithm (LMA)[1] provides a numerical solution to the problem of minimizing a function, generally nonlinear, over a space of parameters of the function. These minimization problems arise… … Wikipedia