Nonconcave penalized M-estimation for the least absolute relative errors model

Ruiya Fan, Shuguang Zhang and Yaohua Wu

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 4, 1118-1135

Abstract: In this paper, we propose a nonconcave penalized M-estimation of the least absolute relative errors (penalized M-LARE) method for a sparse multiplicative regression model, where the dimension of model can increase with the sample size. Under certain appropriate conditions, the consistency and asymptotic normality for the penalized M-LARE estimator are established. Simulations and a real data analysis are in support of our theoretical results and illustrate that the proposed method performs well.

Date: 2023
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DOI: 10.1080/03610926.2021.1923749

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