Robust Signal Recovery for High-Dimensional Linear Log-Contrast Models with Compositional Covariates
含成分协变量的高维线性对数对比模型稳健信号恢复
In this article, we propose a robust signal recovery method for high-dimensional linear log-contrast models, when the error distribution could be heavy-tailed and asymmetric. The proposed method is built on the Huber loss with ℓ1 penalization. We establish the ℓ1 and ℓ2 consistency for the resulting estimator. Under conditions analogous to the irrepresentability condition and the minimum signal strength condition, we prove that the signed support of the slope parameter…