homoscedastic


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homoscedastic

[‚hä·mō·skə¦das·tik]
(statistics)
Pertaining to two or more distributions whose variances are equal.
Pertaining to a variate in a bivariate distribution whose variance is the same for all values of the other variate.
References in periodicals archive ?
The lack of replication means that the researcher must also assume that the errors in y and x are homoscedastic. For this case study, we chose to use data from ILPP and the DEDJTR Macleod quality control program (Table 2).
This equation also indicates that, regardless whether [[sigma].sub.[theta]] is homoscedastic or heteroscedastic, the expected value of the conduct term is observation specific as it depends on firms' market shares.
For [lambda] = 0, we have the homoscedastic model as particular case (for more details see Mazucheli, Souza, & Philippsen, 2011).
As for age and platelet count (i.e., variables that were homoscedastic according to Levene's test), we used the one-way ANOVA to check for any association between these variables and PVT status.
Usually, the assumptions "independent concentration variable x is error-free or less than one-tenth of the error in the dependent response variable y" and "error in y is homoscedastic" (i.e., equal errors for all y values) are not satisfied and, therefore, more sophisticated and statistically coherent regression procedures, such as weighted leastsquares linear regression (WLR) models, should be used [4-18].
There was a reasonable random distribution in test-retest residuals for HRV[T.sub.1] and HRV[T.sub.2], thus suggesting a homoscedastic distribution as a function of the speed.
The White test for the fixed- effects model is based on the null hypothesis that the variance is homoscedastic (constant variance).
The results given in table three clearly shows the presence of heteroscedasticity by rejecting the null hypothesis of homoscedastic standard errors.
The Engel and Granger method is applicable only when the cointegrating equation as the Equation (1) is homoscedastic. On the contrary, if the cointegrating equation is heteroscedastic, the heteroscedastic cointegrating relationship is modelled using the standard generalized autoregressive conditional heteroscedasticity (GARCH) model as shown in the equation below:
According to their results, in the balanced homoscedastic scenario, the methods identified the same point; in the remaining scenarios (i.e., unbalanced homoscedastic and balanced/unbalanced heteroscedastic scenarios), the methods identified different cut-points.
The data passed the ANOVA assumptions (normally distributed, homoscedastic, and equal sample variances) as per the Shapiro-Wilks test, the Breusch-Pagan test, and Levene's test, respectively.
The Ljung-Box test yielded a P value of 0.7799 indicating that the model was free from serial correlation while the ARCH-LM (P = 0.07685) test revealed that model residuals were homoscedastic.