3 papers
stat.ME2026
MATCH: Multiplier-Assisted Tests for Conditional Hypotheses in Non-Euclidean Data
Leheng Cai, Xu Guo, Qirui Hu
We propose a new procedure MATCH (Multiplier-Assisted Tests for Conditional Hypotheses) to test whether the non-Euclidean data match the target model, which is a general framework…
stat.ME2025
Adaptive adequacy testing of high-dimensional factor-augmented regression model
Yanmei Shi, Leheng Cai, Xu Guo +1
In this paper, we investigate the adequacy testing problem of high-dimensional factor-augmented regression model. Existing test procedures perform not well under dense alternatives…
stat.ME2025
Statistical inference for high-dimensional convoluted rank regression
Leheng Cai, Xu Guo, Heng Lian +1
High-dimensional penalized rank regression is a powerful tool for modeling high-dimensional data due to its robustness and estimation efficiency. However, the non-smoothness of the…