High breakdown point robust estimators with missing data

Florencia Statti, Mariela Sued and Victor J. Yohai

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 21, 5145-5162

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 vector x is observed and that y and x 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.

Date: 2018
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DOI: 10.1080/03610926.2017.1388396

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