Mihyun Kim's research is partially supported by NSF grant DMS-2413516, "Measuring extremal dependence of functional data'' (sole PI).


Publications

Published
  • Kim, M., & Kokoszka, P. (2025). Extremal correlation coefficient for functional data. Biometrika, https://doi.org/10.1093/biomet/asaf077. 
  • Kim, M., Kokoszka, P. & Rice, G. (2024). Projection-based white noise and goodness-of-fit tests for functional time series. Statistical Inference for Stochastic Processes, 27, 693-724.
  • Kim, M., Kokoszka, P. & Rice, G. (2023). White noise testing for functional time series. Statistics Surveys, 17, 119-168.
  • Kim, M. & Kokoszka, P. (2023). Asymptotic and finite sample properties of Hill-type estimators in the presence of errors in observations. Journal of Nonparametric Statistics, 35, 1-187.
  • Kim, M., & Kokoszka, P. (2022). Extremal dependence measure for functional data. Journal of Multivariate Analysis, 189, 104887.
  • Nigg, C., Nigg, C., Kim, M., Sharp, J., Burg, X., & Cunningham-Sabo, L. (2021). How should we choose the most appropriate Epoch-Length for Children’s Physical Activity? Proceedings from the 8th International Society for Physical Activity and Health Congress, 14(3).
  • Kim, M., & Kokoszka, P. (2020). Consistency of the Hill estimator for time series observed with measurement errors. Journal of Time Series Analysis, 41, 421–435.
  • Kim, M., & Kokoszka, P. (2019). Hill estimator of projections of functional data on principal components. Statistics, 53, 699–720.
Under review
  • Kim, M., & Lee, J. (2026+). Hypothesis testing for partial tail correlation in multivariate extremes. submitted .

R packages

  • wwntests: this package provides an array of white noise hypothesis tests for functional data and related visualizations (maintainer and co-author).
  • FTSgof: this package offers comprehensive tools for the analysis of functional time series data, focusing on white noise hypothesis testing and goodness-of-fit evaluations (maintainer and co-author).

Selected talks

  • NSF@75 Conference, ASA, Virtual, 2025.
  • International Conference on Extremes, Statistics and Quantitative Risk Management, Fudan University, China, 2024.
  • The Sixth ICSA-Canada Chapter Symposium, Niagara Falls, Canada, 2024.
  • Computational and Methodological Statistics, King's College London, 2022.