Variable selection via RIVAL (removing irrelevant variables amidst lasso iterations) and its application to nuclear material detection

DOI10.1016/j.automatica.2012.06.051zbMath1257.93091OpenAlexW2016301820MaRDI QIDQ1937489

Kung-Sik Chan, Paul Kump, Bill Eichinger, Kang Li, Er-wei Bai

Publication date: 1 March 2013

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2012.06.051

zbMATH Keywords

model selectionnuclear material detection applicationpositive lassoRIVAL

Mathematics Subject Classification ID

Related Items (7)

Penalized and constrained LAD estimation in fixed and high dimension ⋮ Nonparametric estimation of the random coefficients model: an elastic net approach ⋮ Forward and backward least angle regression for nonlinear system identification ⋮ Robust tracking of piecewise linear trajectories with binary sensor networks ⋮ Sparse estimation from noisy observations of an overdetermined linear system ⋮ Testing for shielding of special nuclear weapon materials ⋮ Algorithms for Fitting the Constrained Lasso

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