Lixing Zhu
Biographic Data
| ID | 8920640 |
|---|---|
| NAME | Lixing Zhu |
| GIVEN NAMES | Lixing |
| FAMILY NAME | Zhu |
| SIGNATURE | ZHU L |
| AFFILIATIONS | Department of Mathematics, Hong Kong Baptist University, Hong Kong, China, and School of Statistics, Beijing Normal Univeristy, Beijing, China() |
| ORCID | 0000-0003-1611-4267 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Specification Testing of Regression Models with Mixed Discrete and Continuous Predictors
This article proposes a nonparametric projection-based adaptive-to-model specification test for regressions with discrete and continuous predictors. The test statistic is asymptotically normal under the null hypothesis and omnibus against alternative hypotheses. The test behaves like a locally smoothing test as if the number of continuous predictors was one and can detect the local alternative hypotheses distinct from the null hypothesis at the r…
Single-Index-Based CoVaR With Very High-Dimensional Covariates
Systemic risk analysis reveals the interdependencies of risk factors especially in tail event situations. In applications the focus of interest is on capturing joint tail behavior rather than a variation around the mean. Quantile and expectile regression are used here as tools of data analysis. When it comes to characterizing tail event curves one faces a dimensionality problem, which is important for CoVaR (Conditional Value at Risk) determinati…
No prominent works on this page.
Single-Index-Based CoVaR With Very High-Dimensional Covariates
Systemic risk analysis reveals the interdependencies of risk factors especially in tail event situations. In applications the focus of interest is on capturing joint tail behavior rather than a variation around the mean. Quantile and expectile regression are used here as tools of data analysis. When it comes to characterizing tail event curves one faces a dimensionality problem, which is important for CoVaR (Conditional Value at Risk) determinati…
Specification Testing of Regression Models with Mixed Discrete and Continuous Predictors
This article proposes a nonparametric projection-based adaptive-to-model specification test for regressions with discrete and continuous predictors. The test statistic is asymptotically normal under the null hypothesis and omnibus against alternative hypotheses. The test behaves like a locally smoothing test as if the number of continuous predictors was one and can detect the local alternative hypotheses distinct from the null hypothesis at the r…
Computer Science (2 works) · Econometrics (2 works) · Mathematics (2 works) · Statistical Methods and Inference (2 works) · Advanced Statistical Methods and Models (1 work) · Applied Mathematics (1 work) · Artificial Intelligence (1 work) · Covariate (1 work) · Curse of dimensionality (1 work) · Data mining (1 work)