High breakdown point robust estimators with missing data. Issue 21 (2nd November 2018)

• Record Type: Journal Article
• Authors: Statti, Florencia; Sued, Mariela; Yohai, Victor J.
• Is Part Of: Communications in statistics. Volume 47:Issue 21(2018)
• Page Start: 5145
• Page End: 5162
• Publication Date: 2018-11-02
• Subjects: Asymptotic distribution -- breakdown point -- location and dispersion functionals -- missing at random -- quantiles; 62F35; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2017.1388396
• Languages: English
• ISSNs: 0361-0926

Abstract

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.