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Robust mixture regression based on the skew t distribution (1512.00377v1)

Published 1 Dec 2015 in math.ST, stat.ME, and stat.TH

Abstract: In this study, we propose a robust mixture regression procedure based on the skew t distribution to model heavy-tailed and/or skewed errors in a mixture regression setting. Using the scale mixture representation of the skew t distribution, we give an Expectation Maximization (EM) algorithm to compute the maximum likelihood (ML) estimates for the paramaters of interest. The performance of proposed estimators is demonstrated by a simulation study and a real data example.

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