5 papers
Distributed Selective Inference for Quantile Regression
Xiaohui Yuan, Jiahan Teng, Yan Zhou
We propose a distributed selective inference framework tailored for high-dimensional quantile regression. To enable valid post-selection inference in this context, we address the c…
Distributed Convolutional Rank Regression over Decentralized Networks
Chunjing Li, Tiange Zhao, Xiaohui Yuan
This paper studies convolution rank regression (CRR) over decentralized distributed learning networks. We propose a novel decentralized CRR framework, in which estimators are obtai…
Optimal Poisson subsampling for quantile regression with large-scale longitudinal data
Chunjing Li, Jiahui Zhang, Xiaohui Yuan
To address the computational challenges arising from large-scale longitudinal data, an optimal Poisson subsampling algorithm is proposed for quantile regression. The proposed metho…
Optional subsampling for generalized estimating equations in growing-dimensional longitudinal Data
Chunjing Li, Jiahui Zhang, Xiaohui Yuan
As a powerful tool for longitudinal data analysis, the generalized estimating equations have been widely studied in the academic community. However, in large-scale settings, this a…
Optimal subsampling for functional composite quantile regression in massive data
Jingxiang Pan, Xiaohui Yuan
As computer resources become increasingly limited, traditional statistical methods face challenges in analyzing massive data, especially in functional data analysis. To address thi…