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Metoda naјmaњih kvadrata sa težinama (WLS)×Vajtov test za heteroskedastičnost×
OblastStatistikaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka19351980
TvoracAlexander Craig AitkenHalbert White
TipWeighted linear estimatorGeneral test for heteroskedasticity
Temeljni izvorAitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗
Drugi naziviWLS, weighted regression, heteroscedasticity-corrected OLS, variance-weighted least squaresWhite's general heteroskedasticity test, White değişen varyans testi
Srodne33
SažetakWeighted Least Squares is a generalization of Ordinary Least Squares (OLS) regression that assigns each observation a weight inversely proportional to its error variance, thereby down-weighting high-variance data points and up-weighting precise ones. Introduced in its general matrix form by Alexander Craig Aitken in 1935, WLS is the canonical remedy when heteroscedasticity is present and the error variance structure is known or can be reliably estimated.The White test, introduced by Halbert White in 1980, is a general test for heteroskedasticity that makes no assumption about its functional form. It regresses the squared OLS residuals on the regressors, their squares, and their cross-products, so it can detect heteroskedasticity related to any of these terms. The same 1980 paper introduced the heteroskedasticity-consistent ('White') standard errors that are the standard remedy when the test rejects.
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ScholarGateUporedite metode: Weighted Least Squares · White Test. Preuzeto 2026-06-19 sa https://scholargate.app/sr/compare