2 citations · 3 across the 3 of their papers we have counts for
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High-Dimensional Sparse Single-Index Regression Via Hilbert-Schmidt Independence Criterion
Runxiong Wu, Chang Deng, Xin Chen
Hilbert-Schmidt Independence Criterion (HSIC) has recently been used in the field of single-index models to estimate the directions. Compared with some other well-established metho…
Sufficient Dimension Reduction for Classification
Xin Chen, Jingjing Wu, Zhigang Yao +1
We propose a new sufficient dimension reduction approach designed deliberately for high-dimensional classification. This novel method is named maximal mean variance (MMV), inspired…
Generalized Linear Model for Gamma Distributed Variables via Elastic Net Regularization
Xin Chen, Aleksandr Y. Aravkin, R. Douglas Martin
The Generalized Linear Model (GLM) for the Gamma distribution (glmGamma) is widely used in modeling continuous, non-negative and positive-skewed data, such as insurance claims and…
High Dimensional Elliptical Sliced Inverse Regression in non-Gaussian Distributions
Jia Zhang, Xin Chen, Wang Zhou
Sliced inverse regression (SIR) is the most widely-used sufficient dimension reduction method due to its simplicity, generality and computational efficiency. However, when the dist…
Distribution Regression
Xin Chen, Xuejun Ma, Wang Zhou
Linear regression is a fundamental and popular statistical method. There are various kinds of linear regression, such as mean regression and quantile regression. In this paper, we…