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व्हाइट टेस्ट फॉर हेटेरोस्केडेस्टिसिटी×साधारण न्यूनतम वर्ग (OLS) समाश्रयण×
क्षेत्रअर्थमितिअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष19802019
प्रवर्तकHalbert WhiteWooldridge (textbook treatment); classical least squares
प्रकारGeneral test for heteroskedasticityLinear regression
मौलिक स्रोतWhite, 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
उपनामWhite's general heteroskedasticity test, White değişen varyans testiordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
संबंधित35
सारांशThe 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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