2 citations · 2 across the 7 of their papers we have counts for
8 papers · 1 filter
Sparse Rank Regression for Restricted-Access Economic Data
Wen Zhang, Songshan Yang, Liping Zhu
Empirical research in economics increasingly relies on restricted-access data held by multiple firms or agencies, making it impossible to construct the estimator of interest on the…
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…
Collaborative Inference for Sparse High-Dimensional Models with Non-Shared Data
Yifan Gu, Hanfang Yang, Songshan Yang +1
In modern data analysis, statistical efficiency improvement is expected via effective collaboration among multiple data holders with non-shared data. In this article, we propose a…
Cost-aware Portfolios in a Large Universe of Assets
Qingliang Fan, Marcelo C. Medeiros, Hanming Yang +1
This paper considers the finite horizon portfolio rebalancing problem in terms of mean-variance optimization, where decisions are made based on current information on asset returns…
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…
Double-Estimation-Friendly Inference for High-Dimensional Measurement Error Models with Non-Sparse Adaptability
Shijie Cui, Xu Guo, Songshan Yang +1
In this paper, we introduce an innovative testing procedure for assessing individual hypotheses in high-dimensional linear regression models with measurement errors. This method re…
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…
Kernel Angle Dependence Measures for Complex Objects
Yilin Zhang, Songshan Yang
Measuring and testing dependence between complex objects is of great importance in modern statistics. Most existing work relied on the distance between random variables, which inev…