Abstract
Deepest regression (DR) is a method for linear regression introduced by Rousseeuw and Hubert (1999). The DR is defined as the fit with largest regression depth relative to the data. DR is a robust regression method. We construct an approximate algorithm for fast computation of DR in more than two dimensions. We also construct simultaneous confidence regions for the true unknown parameters, based on bootstrapped estimates.
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Rousseeuw, P.J., Van Aelst, S. (2000). An algorithm for deepest multiple regression. In: Bethlehem, J.G., van der Heijden, P.G.M. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57678-2_13
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DOI: https://doi.org/10.1007/978-3-642-57678-2_13
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1326-5
Online ISBN: 978-3-642-57678-2
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