rrat: Robust Regression with Asymmetric Heavy-Tail Noise Distributions
Implementation of Robust Regression tailored to deal with Asymmetric noise Distribution, which was originally proposed by Takeuchi & Bengio & Kanamori (2002) <doi:10.1162/08997660260293300>. In addition, this implementation is extended as introducing potential feature regularization by LASSO etc.
||R (≥ 2.10), quantreg
||Yi He and Yuelin Zhao
||Yi He <yi.he at stats.oxon.org>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
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