White Test
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Beschrijving
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In statistics, the White test, named after Halbert White, is a test that establishes whether the residual variance of a variable in a regression model is constant (homoscedasticity). To test for constant variance one regresses the squared residuals from a regression model onto the regressors, the cross-products of the regressors and the squared regressors. One then inspects the R2. If homoskedasticity is rejected one can use a GARCH model. An interesting fact is that the paper that published White's test, "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Hetereoskedasticity" (1980) is one of the most cited articles in Economics journals
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In statistics, the White test, named after Halbert White, is a test that establishes whether the residual variance of a variable in a regression model is constant (homoscedasticity). To test for constant variance one regresses the squared residuals from a regression model onto the regressors, the cross-products of the regressors and the squared regressors. One then inspects the R2. If homoskedasticity is rejected one can use a GARCH model. An interesting fact is that the paper that published White's test, "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Hetereoskedasticity" (1980) is one of the most cited articles in Economics journals
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