Heteroskedastic

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Heteroskedastic

A sequence of variables in which each variable has a different variance. Heteroskedastics may be used to measure the margin of the error between predicted and actual data. See also: ARCH.
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Heteroskedasticity consistent covariance matrix estimator and a direct test of heteroskedasticity.
We correct the standard errors for heteroskedasticity and autocorrelation, using the Newey-West (1987) covariance matrix.
Cifter (2012) investigates the performance of an asymmetric normal mixture generalized autoregressive conditional heteroskedasticity (NM-GARCH) model with benchmark GARCH type models.
Table 7 presents results of standard diagnostic tests to check serial correlation, heteroskedasticity and normality of residuals along with correct specification of the model.
7031 Table 8: Heteroskedasticity Test Heteroskedasticity Test: Breusch-Pagan-Godfrey F-statistic 0.
Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation", Econometrica, Vol.
c) Standard errors are corrected for heteroskedasticity.
The results of these tests indicate that the residual is normally distributed and there is also no problem of serial correlation and autoregressive conditional heteroskedasticity.
Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models.
In addition to heteroskedasticity and autocorrelation, one more issue that emerged with respect to the data was the distribution of the dependent variable.
The problem of heteroskedasticity and endogeneity can exist in the regression analysis.