Modelling Variance Heterogeneity: Residual Maximum Likelihood and Diagnostics
研究了正态回归模型中方差随解释变量对数线性变化时的检测、估计和同质性检验，比较了全最大似然与残差最大似然方法，并讨论了基于案例删除和对数似然位移的回归诊断方法。
SUMMARY The assumption of equal variance in the normal regression model is not always appropriate. to attempt to eliminate unequal variance a transformation is often used but if the transformation is not successful, or the variances are of intrinsic interest, it may be necessary to model the variances in some way. We consider the normal regression model when log-linear dependence of the variances on explanatory variables is suspected. Detection of the dependence, estimation and tests of homogeneity based on full and residual maximum likelihood are discussed as are regression diagnostic methods based on case deletion and log-likelihood displacement. Whereas the behaviour of full and residual maximum likelihood is similar under case deletion, changes in residual maximum likelihood estimates and log-likelihood displacements tend to be smaller than maximum likelihood.