3 papers
stat.ME2026
Distributed Convoluted Rank Regression for Non-Shareable Data under Non-Additive Losses
Wen Zhang, Liping Zhu, Songshan Yang
We study high-dimensional rank regression when data are distributed across multiple machines and the loss is a non-additive U-statistic, as in convoluted rank regression (CRR). Cla…
stat.ME2024
Robust Inference for High-dimensional Linear Models with Heavy-tailed Errors via Partial Gini Covariance
Yilin Zhang, Songshan Yang, Yunan Wu +1
This paper introduces the partial Gini covariance, a novel dependence measure that addresses the challenges of high-dimensional inference with heavy-tailed errors, often encountere…
stat.ME2024
High-dimensional log contrast models with measurement errors
Wenxi Tan, Lingzhou Xue, Songshan Yang +1
High-dimensional compositional data are frequently encountered in many fields of modern scientific research. In regression analysis of compositional data, the presence of covariate…