Abstract
Several iterative procedures to solve numerically the problem of robust multiple regression have been proposed in Huber (1972), Huber and Dutter (1974) and Dutter (1977a). According to Dutter (1977b), the H-algorithm distinguished itself for its programming simplicity and rapid computation. The H-algorithm was adapted to the problem of bounded influence regression by Marazzi (1980) and introduced in ROBETH. A similar adaptation was also described by Samarov and Welsch (1982) and introduced in TROLL. Experience shows that when high influential leverage points are present the convergence of the H-algorithm is very poor and the reliability of the result is doubtful. In this paper, alternative procedures with better convergence are discussed. These procedures have been implemented in ROBSYS, a conversational package for robust statistical computing (see Marazzi and Randriamiharisoa (1985)).
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© 1986 Physica-Verlag, Heidelberg for IASC (International Association for Statistical Computing)
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Marazzi, A. (1986). On the Numerical Solutions of Bounded Influence Regression Problems. In: De Antoni, F., Lauro, N., Rizzi, A. (eds) COMPSTAT. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-46890-2_18
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DOI: https://doi.org/10.1007/978-3-642-46890-2_18
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-0355-6
Online ISBN: 978-3-642-46890-2
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