iterative weighted least squares
- iterative weighted least squares
French\ \ des moindres carrés pesé itératif
German\ \ iterativ-gewichtete kleinste Quadrate
Dutch\ \ iteratief gewogen kleinste kwadraten
Italian\ \ di minimi quadrati appesantito iterativo
Spanish\ \ minimos cuadraticos cargados iterativos
Catalan\ \ mínims quadrats ponderats iterat(iu)s
Portuguese\ \ mínimos quadrados ponderados iterativos
Romanian\ \ -
Danish\ \ -
Norwegian\ \ -
Swedish\ \ iterativ vägd minsta-kvadratmetod
Greek\ \ επαναληπτικά σταθμισμένα ελάχιστα τετράγωνα
Finnish\ \ iteratiivisesti painotettu pienimmän neliösumman menetelmä
Hungarian\ \ -
Turkish\ \ yinelemeli ağırlıklı en küçük kareler
Estonian\ \ -
Lithuanian\ \ -
Slovenian\ \ -
Polish\ \ -
Russian\ \ вычисления путем наименьших квадратов с итерационным взвешиванием
Ukrainian\ \ -
Serbian\ \ итеративни пондерисани најмањи квадрати
Icelandic\ \ endurtekningu vegið kosti ferninga
Euskara\ \ etorriko ponderatu karratu txikienen
Farsi\ \ -
Persian-Farsi\ \ کمترین توانهای دوم بازموزون تکراری
Arabic\ \ المربعات الصغرى الموزونة التكرارية
Afrikaans\ \ iteratiewe geweegde kleinste kwadrate
Chinese\ \ -
Korean\ \ 반복가중최소제곱
Statistical terms.
2014.
Look at other dictionaries:
Iteratively 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… … Wikipedia
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
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
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
Linear least squares/Proposed — Linear least squares is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to observations obtained from experiments. Mathematically, it can be stated as the problem of… … Wikipedia
Least absolute deviations — (LAD), also known as Least Absolute Errors (LAE), Least Absolute Value (LAV), or the L1 norm problem, is a mathematical optimization technique similar to the popular least squares technique that attempts to find a function which closely… … Wikipedia
Linear regression — Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… … Wikipedia
Nonlinear regression — See Michaelis Menten kinetics for details In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or… … Wikipedia
Local regression — LOESS, or locally weighted scatterplot smoothing, is one of many modern modeling methods that build on classical methods, such as linear and nonlinear least squares regression. Modern regression methods are designed to address situations in which … Wikipedia
Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… … Wikipedia
