Robust estimation of fixed effect parameters and variances of linear mixed models: the minimum density power divergence approach

Many real-life data sets can be analyzed using linear mixed models (LMMs). Since these are ordinarily based on normality assumptions, under small deviations from the model the inference can be highly unstable when the associated parameters are estimated by classical methods. On the other hand, the d...

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