| Dimension reduction for nonelliptically distributed predictors B Li, Y Dong | 145 | 2009 |
| Dimension reduction for non-elliptically distributed predictors: second-order methods Y Dong, B Li Biometrika 97 (2), 279-294, 2010 | 94 | 2010 |
| Toward further understanding the market‐sensing capability–value creation relationship N Bharadwaj, Y Dong Journal of Product Innovation Management 31 (4), 799-813, 2014 | 61 | 2014 |
| On marginal sliced inverse regression for ultrahigh dimensional model-free feature selection Z Yu, Y Dong, J Shao | 27 | 2016 |
| Predicting innovation success in the motion picture industry: The influence of multiple quality signals N Bharadwaj, CH Noble, A Tower, LM Smith, Y Dong Journal of Product Innovation Management 34 (5), 659-680, 2017 | 26 | 2017 |
| Trace pursuit: A general framework for model-free variable selection Z Yu, Y Dong, LX Zhu Journal of the American Statistical Association 111 (514), 813-821, 2016 | 26 | 2016 |
| Semiparametric estimation of conditional heteroscedasticity via single-index modeling L Zhu, Y Dong, R Li Statistica Sinica 23 (3), 1215, 2013 | 23 | 2013 |
| Robust inverse regression for dimension reduction Y Dong, Z Yu, L Zhu Journal of Multivariate Analysis 134, 71-81, 2015 | 21 | 2015 |
| Sufficient dimension reduction via principal L support vector machine A Artemiou, Y Dong | 20 | 2016 |
| A brief review of linear sufficient dimension reduction through optimization Y Dong Journal of Statistical Planning and Inference 211, 154-161, 2021 | 18 | 2021 |
| Sparse representation classification beyond ℓ1 minimization and the subspace assumption C Shen, L Chen, Y Dong, CE Priebe IEEE Transactions on Information Theory 66 (8), 5061-5071, 2020 | 14 | 2020 |
| Model-free coordinate test and variable selection via directional regression Z Yu, Y Dong Statistica Sinica, 1159-1174, 2016 | 14 | 2016 |
| Real-time sufficient dimension reduction through principal least squares support vector machines A Artemiou, Y Dong, SJ Shin Pattern Recognition 112, 107768, 2021 | 12 | 2021 |
| High-dimensional interactions detection with sparse principal hessian matrix CY Tang, EX Fang, Y Dong The Journal of Machine Learning Research 21 (1), 665-689, 2020 | 9 | 2020 |
| General directional regression Z Yu, Y Dong, M Huang Journal of Multivariate Analysis 124, 94-104, 2014 | 7 | 2014 |
| On sufficient dimension reduction with missing responses through estimating equations Y Dong, Q Xia, CY Tang, Z Li Computational Statistics & Data Analysis 126, 67-77, 2018 | 6 | 2018 |
| On permutation tests for predictor contribution in sufficient dimension reduction Y Dong, C Yang, Z Yu Journal of Multivariate Analysis 149, 81-91, 2016 | 6 | 2016 |
| On sufficient dimension reduction via principal asymmetric least squares AN Soale, Y Dong Journal of Nonparametric Statistics 34 (1), 77-94, 2022 | 5 | 2022 |
| Construction of uniform designs and complex-structured uniform designs via partitionable t-designs H Huang, H Yu, MQ Liu, D Wu Statistica Sinica 31 (4), 1689-1706, 2021 | 5 | 2021 |
| Direction estimation in the single-index model with missing values Y Dong, L Zhu Statistics and its Interface 6 (3), 379-385, 2013 | 5 | 2013 |
Bing LiProfessor of Statistics, Pennsylvania State UniversityVerified email at stat.psu.edu
