A robust regression methodology is proposed via M-estimation. The approach adapts to the tail behavior and skewness of the distribution of the random error terms, providing for a reliable analysis under a broad class of distributions. This is accomplished by allowing the objective function, used to determine the regression parameter estimates, to be selected in a data driven manner. The asymptotic properties of the proposed estimator are established and a numerical algorithm is provided to implement the methodology. The finite sample performance of the proposed approach is exhibited through simulation and the approach was used to analyze two motivating datasets.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167755 | PMC |
| http://dx.doi.org/10.1080/03610926.2018.1423698 | DOI Listing |
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