विधियों की तुलना करें

	साधारण न्यूनतम वर्ग (OLS) समाश्रयण	व्हाइट टेस्ट फॉर हेटेरोस्केडेस्टिसिटी
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	2019	1980
प्रवर्तक	Wooldridge (textbook treatment); classical least squares	Halbert White
प्रकार	Linear regression	General test for heteroskedasticity
मौलिक स्रोत	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.
उपनाम	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu	White's general heteroskedasticity test, White değişen varyans testi
संबंधित	5	3
सारांश	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).	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.