6 papers
Testing for Peer Effects in Heteroskedastic Fixed-Effects Panels
Leheng Cai, Weijia Li, Xu Guo
We study testing for peer effects in linear panel models with individual and time fixed effects when the interaction network is unspecified. We propose a quadratic-form test based…
Multicollinearity-agnostic feature screening for non-Euclidean responses: a factor adjusted approach
Moshu Xu, Leheng Cai, Yanmei Shi +3
In high-dimensional settings, multicollinearity is a pervasive issue that can substantially impair the performance of feature screening methods based on marginal Fréchet regression…
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…
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…
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…
Test and Measure for Partial Mean Dependence Based on Machine Learning Methods
Leheng Cai, Xu Guo, Wei Zhong
It is of importance to investigate the significance of a subset of covariates for the response given covariates in regression modeling. To this end, we propose a signif…