Quadratic approximation on SCAD penalized estimation

Sunghoon Kwon, Hosik Choi and Yongdai Kim

Computational Statistics & Data Analysis, 2011, vol. 55, issue 1, 421-428

Abstract: In this paper, we propose a method of quadratic approximation that unifies various types of smoothly clipped absolute deviation (SCAD) penalized estimations. For convenience, we call it the quadratically approximated SCAD penalized estimation (Q-SCAD). We prove that the proposed Q-SCAD estimator achieves the oracle property and requires only the least angle regression (LARS) algorithm for computation. Numerical studies including simulations and real data analysis confirm that the Q-SCAD estimator performs as efficient as the original SCAD estimator.

Keywords: Penalized; approach; Quadratic; approximation; SCAD; Variable; selection (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:55:y:2011:i:1:p:421-428

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