Homoskedastic

(redirected from Homoskedasticity)
Also found in: Medical.

Homoskedastic

Describing a sequence of variables where each variable has the same or a very similar variance. Homoskedasticity is often assumed in statistics but is not always true. See also: Heteroskedastic.
References in periodicals archive ?
Using White's (1980) general test, all four regressions fail to reject the null hypothesis of homoskedasticity.
For example, Davis and Kanago [9] show that a one-time change in the coefficients of an AR(1) process which is unaccounted for in a regression makes it likely that the null of homoskedasticity will be rejected in favor or ARCH or TVP.
A variance inflation factor test was used for multicollinearity; White's (1980) test failed to reject the hypothesis of homoskedasticity at the 5 percent level of significance.
However, tests for normality and homoskedasticity were easily rejected due to the ARCH effects in the monthly data.
The null hypothesis of homoskedasticity was rejected at a significance level of one percent, in deference to the alternative hypothesis which held that the variance of the error terms was larger in the later years of the sample.
A Breusch-Pagan test rejected the null hypothesis of homoskedasticity in the linear model.
White's test was performed and the chi-squared statistic failed to reject the hypothesis of homoskedasticity at the one- percent significance level.
As noted, this estimator is robust under quite general conditions, so differences between coefficients estimated in STLS compared to OLS or Tobit can be interpreted as evidence of problems of inappropriate clustering at zero, or violation of assumption of homoskedasticity and normality.
Nevertheless, heteroskedasticity remains; Breusch-Pagan tests easily reject homoskedasticity at the 1% level of significance.
White's [51] general heteroskedasticity test rejected the null hypothesis of homoskedasticity at the 1 percent level of significance when applied to the implicit price estimates.
White's (1980) test does not reject homoskedasticity and correct model specification (p = 0.
On the other hand, likelihood ratio tests for groupwise heteroskedasticity consistently reject the null hypothesis of homoskedasticity.