We propose a two stage robust regression procedure to be applied when outliers and leverage points are present. It takes advantage of a high breakdown point MCD estimator and an efficient redescending M-estimator. Its performance was assessed by processing examples from the statistical literature and by carrying out a Monte Carlo simulation experiment; this procedure performs better than other robust regression methods. By pinpointing, labeling and investigating the data generation process of outlying observations, the procedure promotes an interactive attitude in the user and stimulates a thorough scrutiny of data based on subject matter knowledge.

Robust regression analysis : a useful two stage procedure / A. Orenti, E. Marubini. - In: COMMUNICATIONS IN STATISTICS. SIMULATION AND COMPUTATION. - ISSN 0361-0918. - 50:1(2021 Jan 02), pp. 16-37. [10.1080/03610918.2018.1547400]

Robust regression analysis : a useful two stage procedure

A. Orenti
Primo
;
E. Marubini
Ultimo
2021

Abstract

We propose a two stage robust regression procedure to be applied when outliers and leverage points are present. It takes advantage of a high breakdown point MCD estimator and an efficient redescending M-estimator. Its performance was assessed by processing examples from the statistical literature and by carrying out a Monte Carlo simulation experiment; this procedure performs better than other robust regression methods. By pinpointing, labeling and investigating the data generation process of outlying observations, the procedure promotes an interactive attitude in the user and stimulates a thorough scrutiny of data based on subject matter knowledge.
leverage points; MCD estimator; outliers; robust distance; robust regression
Settore MED/01 - Statistica Medica
2-gen-2021
22-gen-2019
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/677771
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