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Regrese metodou ordinárních nejmenších čtverců (OLS)×Bílý test na heteroskedasticitu×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku20191980
TvůrceWooldridge (textbook treatment); classical least squaresHalbert White
TypLinear regressionGeneral test for heteroskedasticity
Původní zdrojWooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗
Další názvyordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuWhite's general heteroskedasticity test, White değişen varyans testi
Příbuzné53
ShrnutíOrdinary 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).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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ScholarGatePorovnat metody: OLS Regression · White Test. Získáno 2026-06-19 z https://scholargate.app/cs/compare