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Yinchu Zhu
Yinchu Zhu
Assistant Professor of Economics, Brandeis University
Verified email at brandeis.edu - Homepage
Title
Cited by
Cited by
Year
An exact and robust conformal inference method for counterfactual and synthetic controls
V Chernozhukov, K WŁthrich, Y Zhu
Journal of the American Statistical Association 116 (536), 1849-1864, 2021
1222021
Linear hypothesis testing in dense high-dimensional linear models
Y Zhu, J Bradic
Journal of the American Statistical Association 113 (524), 1583-1600, 2018
652018
Practical and robust t-test based inference for synthetic control and related methods. arXiv e-prints
V Chernozhukov, K Wuthrich, Y Zhu
arXiv preprint arXiv:1812.10820, 2019
45*2019
Exact and robust conformal inference methods for predictive machine learning with dependent data
V Chernozhukov, K WŁthrich, Z Yinchu
Conference On Learning Theory, 732-749, 2018
452018
Significance testing in non-sparse high-dimensional linear models
Y Zhu, J Bradic
Electronic Journal of Statistics 12 (2), 3312-3364, 2018
40*2018
Distributional conformal prediction
V Chernozhukov, K WŁthrich, Y Zhu
Proceedings of the National Academy of Sciences 118 (48), e2107794118, 2021
302021
Sparsity double robust inference of average treatment effects
J Bradic, S Wager, Y Zhu
arXiv preprint arXiv:1905.00744, 2019
272019
Quantile spacings: A simple method for the joint estimation of multiple quantiles without crossing
L Schmidt, Y Zhu
Available at SSRN 2220901, 2016
192016
Testability of high-dimensional linear models with nonsparse structures
J Bradic, J Fan, Y Zhu
The Annals of Statistics 50 (2), 615-639, 2022
17*2022
Inference for heterogeneous effects using low-rank estimations
V Chernozhukov, CB Hansen, Y Liao, Y Zhu
CEMMAP working paper, 2019
172019
Comparing forecasting performance with panel data
A Timmermann, Y Zhu
CEPR Discussion Paper No. DP13746, 2019
142019
Variable selection in panel models with breaks
SC Smith, A Timmermann, Y Zhu
Journal of econometrics 212 (1), 323-344, 2019
132019
Breaking the curse of dimensionality in regression
Y Zhu, J Bradic
arXiv preprint arXiv:1708.00430, 2017
132017
A projection pursuit framework for testing general high-dimensional hypothesis
Y Zhu, J Bradic
arXiv preprint arXiv:1705.01024, 2017
132017
Inference on average treatment effects in aggregate panel data settings
V Chernozhukov, K WŁthrich, Y Zhu
cemmap working paper, 2019
102019
Two-sample testing in non-sparse high-dimensional linear models
Y Zhu, J Bradic
arXiv preprint arXiv:1610.04580, 2016
82016
Minimax semiparametric learning with approximate sparsity
J Bradic, V Chernozhukov, WK Newey, Y Zhu
arXiv preprint arXiv:1912.12213, 2019
72019
Can Two Forecasts Have the Same Conditional Expected Accuracy?
Y Zhu, A Timmermann
arXiv preprint arXiv:2006.03238, 2020
62020
Do Any Economists Have Superior Forecasting Skills?
R Qu, A Timmermann, Y Zhu
Economists Have Superior Forecasting Skills, 2019
62019
Monitoring forecasting performance
A Timmermann, Y Zhu
62017
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