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White'n testi heteroskedastisuudelle×OLS-regressio (Ordinary Least Squares)×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi19802019
KehittäjäHalbert WhiteWooldridge (textbook treatment); classical least squares
TyyppiGeneral test for heteroskedasticityLinear regression
AlkuperäislähdeWhite, 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
RinnakkaisnimetWhite's general heteroskedasticity test, White değişen varyans testiordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Liittyvät35
TiivistelmäThe 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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ScholarGateVertaile menetelmiä: White Test · OLS Regression. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare