High breakdown point robust estimators with missing data. Issue 21 (2nd November 2018) - Statti, Florencia; Sued, Mariela; Yohai, Victor J.
ABSTRACT: In this paper, we propose a new procedure to estimate the distribution of a variable y when there are missing data. To compensate the presence of missing responses, it is assumed that a covariate vectorx is observed and that y andx are related by means of a semi-parametric regression model. Observed residuals are combined with predicted values to estimate the missing response distribution. Once the responses distribution is consistently estimated, we can estimate any parameter defined through a continuous functional T using a plug in procedure. We prove that the proposed estimators have high breakdown point.