5 papers
Factor Augmented Quantile Regression Model
Xiaoyang Wei, Yanlin Tang, Xu Guo +2
Along with the widespread adoption of high-dimensional data, traditional statistical methods face significant challenges in handling problems with high correlation of variables, he…
Inference of high-dimensional weak instrumental variable regression models without ridge-regularization
Jiarong Ding, Xu Guo, Yanmei Shi +1
Inference of instrumental variable regression models with many weak instruments attracts many attentions recently. To extend the classical Anderson-Rubin test to high-dimensional s…
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…
Estimation and inference of high-dimensional partially linear regression models with latent factors
Yanmei Shi, Meiling Hao, Yanlin Tang +1
In this paper, we introduce a novel high-dimensional Factor-Adjusted sparse Partially Linear regression Model (FAPLM), to integrate the linear effects of high-dimensional latent fa…
High-dimensional inference for single-index model with latent factors
Yanmei Shi, Meiling Hao, Yanlin Tang +2
Models with latent factors recently attract a lot of attention. However, most investigations focus on linear regression models and thus cannot capture nonlinearity. To address this…