Robust inference in generalized partially linear models
- Boente Boente, Graciela Lina
- Rodriguez, Daniela Andrea
DOIAbstract
In many situations, data follow a generalized partly linear model in which the mean of the responses is modeled, through a link function, linearly on some covariates and nonparametrically on the remaining ones. A new class of robust estimates for the smooth function η, associated to the nonparametric component, and for the parameter β, related to the linear one, is defined. The robust estimators are based on a three-step procedure, where large values of the deviance or Pearson residuals are bounded through a score function. These estimators allow us to make easier inferences on the regression parameter β and also improve computationally those based on a robust profile likelihood approach. The resulting estimates of β turn out to be root-n c...
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