Theo dõi
Jinyuan Chang (常晋源)
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
Marginal empirical likelihood and sure independence feature screening
J Chang, CY Tang, Y Wu
The Annals of Statistics 41 (4), 2123-2148, 2013
1172013
Principal component analysis for second-order stationary vector time series
J Chang, B Guo, Q Yao
The Annals of Statistics 46 (5), 2094-2124, 2018
72*2018
High dimensional stochastic regression with latent factors, endogeneity and nonlinearity
J Chang, B Guo, Q Yao
Journal of Econometrics 189 (2), 297-312, 2015
652015
Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity
J Chang, C Zheng, WX Zhou, W Zhou
Biometrics 73 (4), 1300-1310, 2017
642017
Testing for high-dimensional white noise using maximum cross-correlations
J Chang, Q Yao, W Zhou
Biometrika 104 (1), 111-127, 2017
632017
Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering
J Chang, W Zhou, WX Zhou, L Wang
Biometrics 73 (1), 31-41, 2017
622017
A new scope of penalized empirical likelihood with high-dimensional estimating equations
J Chang, CY Tang, TT Wu
The Annals of Statistics 46 (6B), 3185-3216, 2018
602018
High dimensional generalized empirical likelihood for moment restrictions with dependent data
J Chang, SX Chen, X Chen
Journal of Econometrics 185 (1), 283-304, 2015
602015
On the approximate maximum likelihood estimation for diffusion processes
J Chang, SX Chen
The Annals of Statistics 39 (6), 2820-2851, 2011
572011
Local independence feature screening for nonparametric and semiparametric models by marginal empirical likelihood
J Chang, CY Tang, Y Wu
The Annals of Statistics 44 (2), 515-539, 2016
492016
Double-bootstrap methods that use a single double-bootstrap simulation
J Chang, P Hall
Biometrika 102 (1), 203-214, 2015
492015
Confidence regions for entries of a large precision matrix
J Chang, Y Qiu, Q Yao, T Zou
Journal of Econometrics 206 (1), 57-82, 2018
482018
Modelling matrix time series via a tensor CP-decomposition
J Chang, J He, L Yang, Q Yao
Journal of the Royal Statistical Society Series B 85 (1), 127-148, 2023
432023
Central limit theorems for high dimensional dependent data
J Chang, X Chen, M Wu
Bernoulli 30 (1), 712-742, 2024
402024
Estimation of subgraph densities in noisy networks
J Chang, ED Kolaczyk, Q Yao
Journal of the American Statistical Association 117 (537), 361-374, 2022
38*2022
High-dimensional empirical likelihood inference
J Chang, SX Chen, CY Tang, TT Wu
Biometrika 108 (1), 127-147, 2021
292021
Cram\'er-type moderate deviations for Studentized two-sample -statistics with applications
J Chang, QM Shao, WX Zhou
The Annals of Statistics 44 (5), 1931-1956, 2016
272016
An autocovariance-based learning framework for high-dimensional functional time series
J Chang, C Chen, X Qiao, Q Yao
Journal of Econometrics 239 (2), 105385, 2024
222024
Testing the martingale difference hypothesis in high dimension
J Chang, Q Jiang, X Shao
Journal of Econometrics 235 (2), 972-1000, 2023
152023
Optimal covariance matrix estimation for high-dimensional noise in high-frequency data
J Chang, Q Hu, C Liu, CY Tang
Journal of Econometrics 239 (2), 105329, 2024
142024
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