Kuo-Jung Lee

Professor, Department of Statistics and Institute of Data Science, National Cheng Kung University 

Education: University of Minnesota -- Twin Cities

Research: Bayesian Statistics, fMRI Data Analysis, Spatio-Temporal Models

Publications


1.             Robust Bayesian cumulative probit linear mixed models for longitudinal ordinal data. Kuo-Jung Lee, Ray-Bing Chen, and Keunbaik Lee. Computational Statistics, May, 2024. 

2.             Multivariate Probit Linear Mixed Models for Multivariate Longitudinal Binary Data. Kuo-Jung Lee, Chanmin Kim, Jae Keun Yoo, and Keunbaik Lee.  Statistics in Medicine, Online. February, 2024.

3.         DDNAS: Discretized Differentiable Neural Architecture Search for Text Classification. Transactions on Intelligent Systems and Technology. Kuan-Chun Chen, Cheng-Te Li, Kuo-Jung Lee. ACM Transactions on Intelligent Systems and Technology, 15, 5, pp. 1–22, 2023

4.         Use of spatial panel-data models to investigate factors related to incidence of end-stage renal disease: A nationwide longitudinal study in Taiwan. Chien-Chou Su, Kuo-Jung Lee, Chi-Tai Yen, Lu-Hsuan Wu, Chien-Huei Huang, Meng-Zhan Lu & Ching-Lan Cheng. BMC Public Health 23, 247 (2023). https://doi.org/10.1186/s12889-023-15189-7

5.         Robust probit linear mixed models for longitudinal binary data. Kuo-Jung Lee, Chanmin Kim, Ray-Bing Chen, Keunbaik Lee. Biometrical Journal, 1307-1324, 2022

6.         Variable selection in finite mixture of regression models with an unknown number of components.  Lee, K-J., Chen Y-C., & Feldkircher M. Computational Statistics and Data Analysis, 158, June 2021, 107180

7.         Determination of Correlations in Multivariate Longitudinal Data with Modified Cholesky and Hypersphere Decomposition using Bayesian Variable Selection Approach. Lee K-J., Chen, R-B., & Lee KB.  Statistics in Medicine, 978-997, 2021

18.         Bayesian variable selection in a finite mixture of linear mixed-effects models. Lee, K-J. & Chen, R-B., 2019 September 2, Journal of Statistical Computation and Simulation. 89, 13, p. 2434-2453.

9.         Cerebral control of winking before and after learning: An event-related fMRI study. Lin, C. C. K., Lee, K. J., Huang, C. H. & Sun, Y. N., 2019 December 1, Brain and Behavior. 9, 12, e01483.

10.         An instantaneous spatiotemporal model for predicting traffic-related ultrafine particle concentration through mobile noise measurements. Lin, M. Y., Guo, Y. X., Chen, Y. C., Chen, W. T., Young, L. H., Lee, K. J., Wu, Z. Y. & Tsai, P. J., 2018 September 15, Science of the Total Environment. 636, p. 1139-1148.

11.         Of Needles and Haystacks: Revisiting Growth Determinants by Robust Bayesian Variable Selection. Lee, K. J. & Chen, Y. C., 2018 June 1, Empirical Economics. 54, 4, p. 1517-1547 31 p 

12.         Milr: Multiple-instance logistic regression with lasso penalty. Chen, P. Y., Chen, C. C., Yang, C. H., Chang, S-M. & Lee, K-J., 2017 June 1, R Journal. 9, 1, p. 446-457.

13.       On the Determinants of the 2008 Financial Crisis: A Bayesian Approach to the Selection of Groups and Variables.  Chen, R. B., Chen, Y. C., Chu, C. H. & Lee, K. J., 2017 December 20, 於 : Studies in Nonlinear Dynamics and Econometrics. 21, 5, 20160107.

14.       Spatial Bayesian hierarchical model with variable selection to fMRI data. Lee, K. J., Hsieh, S. & Wen, T., 2017 August, Spatial Statistics. 21, p. 96-113.

15.       Bayesian variable selection for finite mixture model of linear regressions. Lee, K. J., Chen, R. B. & Wu, Y. N., 2016 March 1, Computational Statistics and Data Analysis. 95, p. 1-16.

16.       BSGS: Bayesian sparse group selection. Lee, K-J. & Chen, R-B., 2015 January 1, R Journal. 7, 2, p. 122-133.

17.       Spatial Bayesian variable selection models on functional magnetic resonance imaging time-series data. Lee, K. J., Jones, G. L., Caffo, B. S. & Bassett, S. S., 2014 January 1, Bayesian Analysis. 9, 3, p. 699-732.

18.       Bayesian analysis of Box-Cox transformed linear mixed models with ARMA(p, q) dependence. Lee, J. C., Lin, T. I., Lee, K. J. & Hsu, Y. L., 2005 August 1, Journal of Statistical Planning and Inference. 133, 2, p. 435-451.


Teaching