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  2. Heteroskedasticity-consistent standard errors - Wikipedia

    en.wikipedia.org/wiki/Heteroskedasticity...

    An alternative to explicitly modelling the heteroskedasticity is using a resampling method such as the wild bootstrap. Given that the studentized bootstrap, which standardizes the resampled statistic by its standard error, yields an asymptotic refinement, [13] heteroskedasticity-robust standard errors remain nevertheless useful.

  3. Homoscedasticity and heteroscedasticity - Wikipedia

    en.wikipedia.org/wiki/Homoscedasticity_and...

    Thus, regression analysis using heteroscedastic data will still provide an unbiased estimate for the relationship between the predictor variable and the outcome, but standard errors and therefore inferences obtained from data analysis are suspect. Biased standard errors lead to biased inference, so results of hypothesis tests are possibly wrong.

  4. White test - Wikipedia

    en.wikipedia.org/wiki/White_test

    White test is a statistical test that establishes whether the variance of the errors in a regression model is constant: that is for homoskedasticity. This test, and an estimator for heteroscedasticity-consistent standard errors , were proposed by Halbert White in 1980. [ 1 ]

  5. Breusch–Pagan test - Wikipedia

    en.wikipedia.org/wiki/Breusch–Pagan_test

    If the test statistic has a p-value below an appropriate threshold (e.g. p < 0.05) then the null hypothesis of homoskedasticity is rejected and heteroskedasticity assumed. If the Breusch–Pagan test shows that there is conditional heteroskedasticity, one could either use weighted least squares (if the source of heteroskedasticity is known) or ...

  6. Newey–West estimator - Wikipedia

    en.wikipedia.org/wiki/Newey–West_estimator

    In Julia, the CovarianceMatrices.jl package [11] supports several types of heteroskedasticity and autocorrelation consistent covariance matrix estimation including Newey–West, White, and Arellano. In R , the packages sandwich [ 6 ] and plm [ 12 ] include a function for the Newey–West estimator.

  7. Homogeneity and heterogeneity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Homogeneity_and...

    [1] [2] [3] Assuming a variable is homoscedastic when in reality it is heteroscedastic (/ ˌ h ɛ t ər oʊ s k ə ˈ d æ s t ɪ k /) results in unbiased but inefficient point estimates and in biased estimates of standard errors, and may result in overestimating the goodness of fit as measured by the Pearson coefficient.

  8. Best egg alternatives and substitutes amid rising prices ...

    www.aol.com/best-egg-alternatives-substitutes...

    As bird flu cases continue to rise in the U.S., heavily impacting egg-laying flocks, so have the prices on cartons of fresh eggs due to dwindling supply. Egg prices are through the roof, up nearly ...

  9. Autoregressive conditional heteroskedasticity - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_conditional...

    In 2004, Claudia Klüppelberg, Alexander Lindner and Ross Maller proposed a continuous-time generalization of the discrete-time GARCH(1,1) process.The idea is to start with the GARCH(1,1) model equations