5 citations · 12 across the 6 of their papers we have counts for
6 papers
Score function-based tests for ultrahigh-dimensional linear models
Weichao Yang, Xu Guo, Lixing Zhu
In this paper, we investigate score function-based tests to check the significance of an ultrahigh-dimensional sub-vector of the model coefficients when the nuisance parameter vect…
Testing heteroscedasticity for regression models based on projections
Falong Tan, Xuejun Jiang, Xu Guo +1
In this paper we propose a new test of heteroscedasticity for parametric regression models and partial linear regression models in high dimensional settings. When the dimension of…
Heteroscedasticity Testing for Regression Models: A Dimension Reduction-based Model Adaptive
Xuehu Zhu, Fei Chen, Xu Guo +1
Heteroscedasticity testing is of importance in regression analysis. Existing local smoothing tests suffer severely from curse of dimensionality even when the number of covariates i…
A robust adaptive-to-model enhancement test for parametric single-index models
Cuizhen Niu, Lixing Zhu
In the research on checking whether the underlying model is of parametric single-index structure with outliers in observations, the purpose of this paper is two-fold. First, a test…
Enhancements of nonparametric generalized likelihood ratio test: Bias-correction and dimension reduction
Cuizhen Niu, Xu Guo, Lixing Zhu
Nonparametric generalized likelihood ratio test is popularly used for model checking for regressions. However, there are two issues that may be the barriers for its powerfulness. F…
Model checking for generalized linear models: a dimension-reduction model-adaptive approach
Xu Guo, Lixing Zhu
Local smoothing testing that is based on multivariate nonparametric regression estimation is one of the main model checking methodologies in the literature. However, relevant tests…