| Гетероскедастичность |  |
Гетероскедасти́чность — понятие, используемое в прикладной статистике, означающее неоднородность наблюдений, выражающуюся в неодинаковой дисперсии случайной ошибки регрессионной модели. Википедия
The assumption of homoscedasticity (meaning “same variance”) is central to linear regression models. |
Homoskedastic (also spelled "homoscedastic") refers to a condition in which the variance of the residual, or error term, in a regression model is constant. |
Homoscedasticity, or homogeneity of variances, is an assumption of equal or similar variances in different groups being compared. |
2 янв. 2024 г. · Homoscedasticity ensures a uniform variance of residuals across various levels of independent variables, enhancing the precision of parameter ... |
20 нояб. 2024 г. · a situation in which all the variables (= things that can change) in a sequence (= a series of related things) are equal. |
Simply put, homoscedasticity means “having the same scatter.” For it to exist in a set of data, the points must be about the same distance from the line, as ... |
In regression, homoscedasticity refers to a situation where the conditional variance of Y, given X, does not depend on X. |
29 апр. 2024 г. · Homoscedasticity, a fundamental assumption in linear regression models, ensures that the variance of error terms remains constant across all ... |
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