Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1149742 | Journal of Statistical Planning and Inference | 2009 | 22 Pages |
Abstract
In this paper, under a nonparametric regression model, we introduce two families of robust procedures to estimate the regression function when missing data occur in the response. The first proposal is based on a local MM-functional applied to the conditional distribution function estimate adapted to the presence of missing data. The second proposal imputes the missing responses using the local MM-smoother based on the observed sample and then estimates the regression function with the completed sample. We show that the robust procedures considered are consistent and asymptotically normally distributed. A robust procedure to select the smoothing parameter is also discussed.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Graciela Boente, Wenceslao González–Manteiga, Ana Pérez–González,