Kuo‐Jung Lee

416 total citations
28 papers, 266 citations indexed

About

Kuo‐Jung Lee is a scholar working on Statistics and Probability, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Kuo‐Jung Lee has authored 28 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Statistics and Probability, 9 papers in Artificial Intelligence and 9 papers in Economics and Econometrics. Recurrent topics in Kuo‐Jung Lee's work include Statistical Methods and Inference (11 papers), Statistical Methods and Bayesian Inference (9 papers) and Bayesian Methods and Mixture Models (7 papers). Kuo‐Jung Lee is often cited by papers focused on Statistical Methods and Inference (11 papers), Statistical Methods and Bayesian Inference (9 papers) and Bayesian Methods and Mixture Models (7 papers). Kuo‐Jung Lee collaborates with scholars based in Taiwan, South Korea and United States. Kuo‐Jung Lee's co-authors include Ray‐Bing Chen, Susan Spear Bassett, Brian Caffo, Galin L. Jones, Ying‐Lin Hsu, Ying Wu, Jack C. Lee, Tsung‐I Lin, Yu‐Cheng Chen and Ming-Yeng Lin and has published in prestigious journals such as The Science of The Total Environment, Statistics in Medicine and BMC Public Health.

In The Last Decade

Kuo‐Jung Lee

26 papers receiving 260 citations

Peers

Kuo‐Jung Lee
Gregory Gurevich Israel
Wei‐Han Liu China
Matteo Pelagatti Italy
Emanuele Taufer Italy
Joonki Noh United States
Ruijun Bu United Kingdom
Hideo Kozumi Japan
Alexander Szimayer Germany
Christos Agiakloglou Greece
Gregory Gurevich Israel
Kuo‐Jung Lee
Citations per year, relative to Kuo‐Jung Lee Kuo‐Jung Lee (= 1×) peers Gregory Gurevich

Countries citing papers authored by Kuo‐Jung Lee

Since Specialization
Citations

This map shows the geographic impact of Kuo‐Jung Lee's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kuo‐Jung Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuo‐Jung Lee more than expected).

Fields of papers citing papers by Kuo‐Jung Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuo‐Jung Lee. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kuo‐Jung Lee. The network helps show where Kuo‐Jung Lee may publish in the future.

Co-authorship network of co-authors of Kuo‐Jung Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Kuo‐Jung Lee. A scholar is included among the top collaborators of Kuo‐Jung Lee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kuo‐Jung Lee. Kuo‐Jung Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lee, Kuo‐Jung, Chanmin Kim, Jae Keun Yoo, & Keunbaik Lee. (2024). Multivariate probit linear mixed models for multivariate longitudinal binary data. Statistics in Medicine. 43(8). 1527–1548.
2.
3.
Li, Cheng–Te, et al.. (2023). DDNAS: Discretized Differentiable Neural Architecture Search for Text Classification. ACM Transactions on Intelligent Systems and Technology. 14(5). 1–22. 1 indexed citations
4.
Lee, Kuo‐Jung, Chanmin Kim, Ray‐Bing Chen, & Keunbaik Lee. (2022). Robust probit linear mixed models for longitudinal binary data. Biometrical Journal. 64(7). 1307–1324. 2 indexed citations
5.
Lee, Kuo‐Jung, Martin Feldkircher, & Yi‐Chi Chen. (2021). Variable selection in finite mixture of regression models with an unknown number of components. Computational Statistics & Data Analysis. 158. 107180–107180. 2 indexed citations
6.
7.
Lee, Kuo‐Jung. (2019). The effects of social responsibility on company value: a real options perspective of Taiwan companies. Economic Research-Ekonomska Istraživanja. 32(1). 3835–3852. 14 indexed citations
8.
Lee, Kuo‐Jung & Ray‐Bing Chen. (2019). Bayesian variable selection in a finite mixture of linear mixed-effects models. Journal of Statistical Computation and Simulation. 89(13). 2434–2453. 4 indexed citations
9.
Lin, Ming-Yeng, Yu‐Cheng Chen, Wei-Ting Chen, et al.. (2018). An instantaneous spatiotemporal model for predicting traffic-related ultrafine particle concentration through mobile noise measurements. The Science of The Total Environment. 636. 1139–1148. 14 indexed citations
10.
Lee, Kuo‐Jung, et al.. (2018). Contagion Effect of Natural Disaster and Financial Crisis Events on International Stock Markets. Journal of risk and financial management. 11(2). 16–16. 25 indexed citations
11.
Chen, Ray‐Bing, Yi‐Chi Chen, Chi‐Hsiang Chu, & Kuo‐Jung Lee. (2017). On the determinants of the 2008 financial crisis: a Bayesian approach to the selection of groups and variables. Studies in Nonlinear Dynamics and Econometrics. 21(5). 3 indexed citations
12.
Lee, Kuo‐Jung, et al.. (2017). Spatial Bayesian hierarchical model with variable selection to fMRI data. Spatial Statistics. 21. 96–113. 1 indexed citations
13.
Yang, Chun-Hao, et al.. (2017). milr: Multiple-Instance Logistic Regression with Lasso Penalty. The R Journal. 9(1). 446–446. 6 indexed citations
14.
Lee, Kuo‐Jung & Yi‐Chi Chen. (2017). Of needles and haystacks: revisiting growth determinants by robust Bayesian variable selection. Empirical Economics. 54(4). 1517–1547. 2 indexed citations
15.
Lee, Kuo‐Jung & Ray‐Bing Chen. (2015). BSGS: Bayesian Sparse Group Selection. The R Journal. 7(2). 122–122. 4 indexed citations
16.
Lee, Kuo‐Jung, Galin L. Jones, Brian Caffo, & Susan Spear Bassett. (2014). Spatial Bayesian Variable Selection Models on Functional Magnetic Resonance Imaging Time-Series Data. Bayesian Analysis. 9(3). 699–732. 24 indexed citations
17.
Lee, Kuo‐Jung, et al.. (2014). Momentum strategy and credit risk. Applied Financial Economics. 24(11). 753–762. 1 indexed citations
18.
Lee, Kuo‐Jung, et al.. (2012). How to gauge credit risk: an investigation based on data envelopment analysis and the Markov chain model. Applied Financial Economics. 22(11). 887–897. 6 indexed citations
19.
Lee, Kuo‐Jung. (2010). Computational issues in using Bayesian hierarchical methods for the spatial modeling of fMRI data.. University of Minnesota Digital Conservancy (University of Minnesota). 1 indexed citations
20.
Lee, Kuo‐Jung, et al.. (2009). The Valuation of Information Technology Investments by Real Options Analysis. Review of Pacific Basin Financial Markets and Policies. 12(4). 611–628. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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