Courses Taught
- MATH 739/839: Applied Regression Analysis
- MATH 756/856: Princpls Statistical Inference
Research Interests
- Statistics
- Deep Learning
- Time Series Analysis
Selected Publications
Geng, P., & Nguyen, H. (2024). Parameter estimation for Logistic errors-in-variables regression under case–control studies. Statistical Methods & Applications, 33(2), 661-684. doi:10.1007/s10260-023-00737-7
Zhang, S., Zhou, Y., Geng, P., & Lu, Q. (2024). Functional Neural Networks for High-Dimensional Genetic Data Analysis.. IEEE/ACM Trans Comput Biol Bioinform, 21(3), 383-393. doi:10.1109/TCBB.2024.3364614
Geng, P. (2022). Estimation of functional-coefficient autoregressive models with measurement error. Journal of Multivariate Analysis, 192, 105077. doi:10.1016/j.jmva.2022.105077
Geng, P., & Koul, H. L. (2022). Weighted empirical minimum distance estimators in linear errors-in-variables regression models. Journal of Statistical Planning and Inference, 219, 147-174. doi:10.1016/j.jspi.2021.12.007
Koul, H. L., & Geng, P. (2020). Weighted Empirical Minimum Distance Estimators in Berkson Measurement Error Regression Models. In Analytical Methods in Statistics (pp. 31-71). Springer International Publishing. doi:10.1007/978-3-030-48814-7_3
Geng, P., & Koul, H. L. (2019). Minimum distance model checking in Berkson measurement error models with validation data. TEST, 28(3), 879-899. doi:10.1007/s11749-018-0610-6
Geng, P., Tong, X., & Lu, Q. (2019). An integrative U method for joint analysis of multi-level omic data.. BMC Genet, 20(1), 40. doi:10.1186/s12863-019-0742-z
Geng, P., & Koul, H. L. (2017). Model checking in Tobit regression with measurement errors using validation data. Journal of Statistical Planning and Inference, 190, 15-31. doi:10.1016/j.jspi.2017.05.002
Geng, P., & Sakhanenko, L. (2016). Parameter estimation for the logistic regression model under case-control study. Statistics & Probability Letters, 109, 168-177. doi:10.1016/j.spl.2015.11.019
