| Spatial Bayesian variable selection models on functional magnetic resonance imaging time-series data KJ Lee, GL Jones, BS Caffo, SS Bassett Bayesian Analysis (Online) 9 (3), 699, 2014 | 74 | 2014 |
| Bayesian variable selection for finite mixture model of linear regressions KJ Lee, RB Chen, YN Wu Computational statistics & data analysis 95, 1-16, 2016 | 31 | 2016 |
| Bayesian analysis of Box–Cox transformed linear mixed models with ARMA (p, q) dependence JC Lee, TI Lin, KJ Lee, YL Hsu Journal of statistical Planning and Inference 133 (2), 435-451, 2005 | 26 | 2005 |
| An instantaneous spatiotemporal model for predicting traffic-related ultrafine particle concentration through mobile noise measurements MY Lin, YX Guo, YC Chen, WT Chen, LH Young, KJ Lee, ZY Wu, PJ Tsai Science of the total environment 636, 1139-1148, 2018 | 21 | 2018 |
| milr: Multiple-Instance Logistic Regression with Lasso Penalty. PY Chen, CC Chen, CH Yang, SM Chang, KJ Lee R J. 9 (1), 446, 2017 | 8 | 2017 |
| On the determinants of the 2008 financial crisis: A Bayesian approach to the selection of groups and variables RB Chen, YC Chen, CH Chu, KJ Lee Studies in Nonlinear Dynamics & Econometrics 21 (5), 20160107, 2017 | 7 | 2017 |
| BSGS: Bayesian Sparse Group Selection. KJ Lee, RB Chen R Journal 7 (2), 2015 | 7 | 2015 |
| Bayesian variable selection in a finite mixture of linear mixed-effects models KJ Lee, RB Chen Journal of Statistical Computation and Simulation 89 (13), 2434-2453, 2019 | 6 | 2019 |
| Variable selection in finite mixture of regression models with an unknown number of components KJ Lee, M Feldkircher, YC Chen Computational statistics & data analysis 158, 107180, 2021 | 4 | 2021 |
| Determination of correlations in multivariate longitudinal data with modified Cholesky and hypersphere decomposition using Bayesian variable selection approach KJ Lee, RB Chen, MS Kwak, K Lee Statistics in Medicine 40 (4), 978-997, 2021 | 3 | 2021 |
| Cerebral control of winking before and after learning: An event‐related fMRI study CCK Lin, KJ Lee, CH Huang, YN Sun Brain and Behavior 9 (12), e01483, 2019 | 3 | 2019 |
| Of needles and haystacks: revisiting growth determinants by robust Bayesian variable selection KJ Lee, YC Chen Empirical Economics 54, 1517-1547, 2018 | 3 | 2018 |
| Robust probit linear mixed models for longitudinal binary data KJ Lee, C Kim, RB Chen, K Lee Biometrical Journal 64 (7), 1307-1324, 2022 | 2 | 2022 |
| DDNAS: Discretized Differentiable Neural Architecture Search for Text Classification KC Chen, CT Li, KJ Lee ACM Transactions on Intelligent Systems and Technology 14 (5), 1-22, 2023 | 1 | 2023 |
| Spatial Bayesian hierarchical model with variable selection to fMRI data KJ Lee, S Hsieh, T Wen Spatial Statistics 21, 96-113, 2017 | 1 | 2017 |
| Application of Spatial Bayesian Hierarchical Models to fMRI Data KJ Lee Assessment of Cellular and Organ Function and Dysfunction using Direct and …, 2016 | 1 | 2016 |
| Spatial Statistics KJ Lee, S Hsieh, T Wen | | 2017 |
| Finite mixture of regression modeling for exchange market pressures during the financial crisis: A robust Bayesian approach to variable selection KJ Lee, YC Chen 2016 臺灣計量經濟學會年會, 2016 | | 2016 |
| Bayesian approaches to variable selection with highly correlated regressors:: Predictive perspectives from cross-country growth regressions KJ Lee, YC Chen 總體經濟計量模型研討會, 2015 | | 2015 |
| Supplemental Material for Spatial Bayesian Variable Selection Models on Functional Magnetic Resonance Imaging Time-Series Data KJ Lee, GL Jones, BS Caffo, S Bassett | | 2013 |
