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Whitetest för heteroskedasticitet×Vanligaste minsta kvadratmetoden (OLS) Regression×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår19802019
UpphovspersonHalbert WhiteWooldridge (textbook treatment); classical least squares
TypGeneral test for heteroskedasticityLinear regression
UrsprungskällaWhite, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
AliasWhite's general heteroskedasticity test, White değişen varyans testiordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Närliggande35
SammanfattningThe 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.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
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ScholarGateJämför metoder: White Test · OLS Regression. Hämtad 2026-06-17 från https://scholargate.app/sv/compare