科研成果 |
<p> 1. Lin, B., Pang, Z., Zhang, J., Chen, C., Fast feature selection via streamwise procedure for massive data. Brazilian Journal of Probability and Statistics, 36(1): 81-102, 2022. <br>2. Zhang, J., Lin, B.*, Estimation of correlation coefficient with general distortion measurement errors. Communications in Statistics - Simulation and Computation, 1-31, 2021. <br>3. Lin, B. and Pang, Z., Stability of methods for differential expression analysis of RNA-seq data. BMC genomics, 20:35 2019. <br>4. Zhang, J., Lin, B.* and Li, G., Nonlinear regression models with general distortion measurement errors. Journal of Statistical Computation and Simulation 89 (8), 1482-1504, 2019. <br>5. Zhang, J., Gai, Y., Lin, B.* and Zhu, X., Nonlinear regression models with single-index heteroscedasticity. Statistica Neerlandica, 73(2), 292-316, 2019. 6. Lin, B., Pang, Z. and Wang, Q., Cluster feature selection in high dimensional linear models. Random Matrices: Theory and Applications, <br>6: (1750015-1)-(1750015-23), 2018. <br>7. Zhang, J., Zhou, Y., Lin, B.* and Yu, Y., Estimation and hypothesis test on partial linear models with additive distortion measurement errors. Computational Statistics and Data Analysis. 112:114-128, 2017. <br>8. Zhang, J., Chen, Q., Lin, B. * and Zhou, Y., On the single-index model estimate of the conditional density function: consistency and implementation. Journal of Statistical Planning and Inference, 187:56-66, 2017. <br>9. Lin, B., Wang, Q., Zhang, J. and Pang, Z., Stable prediction in high-dimensional linear models. Statistics and Computing, 27:1401-1412, 2017. <br>10. Pang, Z., Lin, B. and Jiang J., Regularization parameter selection via bootstrapping. Australian & New Zealand Journal of Statistics, 58:335-356, 2016.<br><br></p> |
科研项目 |
海量数据下回归模型的变量选择及统计推断研究,国家自然科学基金青年科学基金项目2018/01~2020/12, 23万,主持 <br>高维回归模型的预测稳定性研究,国家自然科学基金数学天元专项基金,2017/01~2017/12, 3万,主持"<br> |