Under Review

Co-first author (equal contribution, alphabetical order); *Corresponding author

  • Lee, J.* and Cooley, D. (2026). Transformed-linear prediction for extremes. [arXiv] [Code]
  • Lee, J.* and Wadsworth, J. (2025). Geometric criteria for identifying extremal dependence and flexible modeling via additive mixtures. [arXiv] [Code]
  • Kim, M. and Lee, J.*† (2025). Hypothesis testing for partial tail correlation in multivariate extremes. [arXiv] [Code]
  • Campbell, R., Grolmusova, K., Kakampakou, L., and Lee, J.*† (2025). Analysing extreme rainfall via a geometric framework. [arXiv]

Peer-Reviewed Publications

  • Lee, J. and Kim, Y. (2026). Structure learning for multivariate extremes: A comparative study of regional UK rainfall. AIMS Mathematics, 11(3). [DOI]
  • Kiriliouk, A., Lee, J., and Segers, J. (2025). X-vine models for multivariate extremes. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 87(3), 579–602. [DOI] [Code]
  • Lee, J.*, Cooley, D., Wagner, A., and Liston, G. (2025). A calibration method for projecting future extremes via a linear mapping of parameters. Environmental and Ecological Statistics, 32, 1–20. [DOI]

Applied and Regional Publications

  • Lee, J., Kim, E. S., and Kim, Y. (2025). A prediction model for heatwaves and tropical nights based on apparent temperature. Journal of the Korean Data & Information Science Society, 36(6), 1057–1067.
  • Hughes, S., Rondeau, M., Shannon, S., Sharp, J., Ivins, G., Lee, J., Taylor, I., and Bendixsen, B. A. (2021). Holistic self-learning approach for young adult depression and anxiety compared to medication-based treatment-as-usual. Community Mental Health Journal, 57(2), 392–402.
  • Lee, J. and Kim, Y. (2016). A spatial analysis of the Neyman-Scott rectangular pulses model using an approximate likelihood function. Journal of the Korean Data & Information Science Society, 27(5), 1119–1131.
  • Gjonbrataj, J., Choi, W.-I., Bahn, Y. E., Rho, B. H., Lee, J. J., and Lee, C. W. (2015). Incidence of idiopathic pulmonary fibrosis in Korea based on the 2011 ATS/ERS/JRS/ALAT statement. The International Journal of Tuberculosis and Lung Disease, 19(6), 742–746.
  • Lee, J., Kim, N. H., Kwon, H. J., and Kim, Y. (2014). A Bayesian analysis of return levels for extreme precipitation in Korea. The Korean Journal of Applied Statistics, 27(6), 947–958.

Dissertations

  • Lee, J., Cooley, D., Kokoszka, P., Breidt, J., and Pezeshki, A. (2022). Linear prediction and partial tail correlation for extremes. Colorado State University. Libraries. [PDF]