homoscedastic

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Related to Homoskedastic: Homoscedastic

homoscedastic

(ˌhəʊməʊskɪˈdæstɪk)
adj
1. (Statistics) (of several distributions) having equal variance
2. (Statistics) (of a bivariate or multivariate distribution) having one variable whose variance is the same for all values of the other or others
3. (Statistics) (of a random variable) having this property
[C20: from homo- + scedastic, from Greek skedasis a scattering, dispersal]
homoscedasticity n
References in periodicals archive ?
One of the defining characteristics of the traditional 3SLS is that the errors are homoskedastic conditional on the instrumental variables.
In order to check the assumption of Heteroscedasticity, residual series are made and test of Heteroskedasticity called White test was conducted to check the null hypothesis that error variances are Homoskedastic in nature.
The residuals of linear regression should then be homoskedastic according to least squares estimator hypothesis.
Then, the generalized least squares (GLS) estimator is run and the residuals will be homoskedastic (Table 6).
TABLE 2 Testing Heteroskedasticity in Presence of Instrumental Variables (Levels of IVs) Null Hypothesis (H0): Disturbance is Homoskedastic Test 2(6) p-values Pagan-Hall General Test Statistic 1.
7), strongly rejecting the null hypothesis that the error terms are homoskedastic.
As for the specification tests for the VAR model, the errors are found serially uncorrelated and homoskedastic.
The null hypothesis of this test was that the error variance was Homoskedastic.
Given the stylized facts of financial time series, examining the weekday effect in mean and variance under the assumption that returns are normally distributed and/or homoskedastic (as postulated in most prior studies) may not be appropriate.
i] represents the normally and homoskedastic distributed error term.
This fixed effects model assumes that the errors are homoskedastic and spatially and temporally independent, obtaining biases estimators when there is dependence and heteroskedasticity problems in the term errors as shown by Beck (2001) and O'Connell (1998).
36) (In the case where residuals are homoskedastic within periods but heteroskedastic across time, adjusted values such as those produced by the nonparametric method proposed by Duan will give estimates that are numerically identical to unadjusted values produced by other methods.