1. Chung, H. C. and Ahn, J. (2021), Randomized Dual Rotations for High-dimensional Outlier Detection, Journal of Multivariate Analysis, accepted. 

  2. Park, J., Ahn, J., and Jeon, Y. (2021), Sparse Functional Linear Discriminant Analysis, Biometrika, accepted.

  3. Xi Fang, Wenwu Sun, Julie Jeon, Michael Azain, Holly Kinder, Jeongyoun Ahn, Hee Cheol Chung, Ryan S. Mote, Nikolay M. Filipov, Qun Zhao, Srujana Rayalam, Hea Jin Park (2020), Perinatal Docosahexaenoic Acid Supplementation Improves Cognition and alters Brain Function Organization in Piglets, Nutrients, accepted

  4. Poythress, J., Kaiser, E., Scheulin, K., Jurgielewicz, B., Lazar, N.,  Park, C., Stice, S., Ahn, J., and West, F. (2020), An integrative multivariate approach for predicting functional recovery in a translational pig ischemic stroke model, Neural Regeneration Research, accepted.
  5. Ahn, J., Chung, H. C. and Jeon, Y. (2020), Trace Regularization for High-dimensional Multi-class Discrimination, Journal of Computational and Graphical Statistics, accepted.
  6. Qiu, D. and Ahn, J. (2019), Grouped Variable Screening for Ultrahigh Dimensional Data Under Linear Model, Computational Statistics and Data Analysis, accepted.
  7. Ahn, J., Lee, M. H., and Lee, J. (2019), Distance-based Outlier Detection for High Dimension, Low Sample Size Data, Journal of Applied Statistics, 46(1), 13--29.
  8. Jung, S., Ahn, J. and Jeon, Y. (2018) Penalized Orthogonal Iteration for Sparse Estimation of Generalized Eigenvalue Problem, Journal of Computational and Graphical Statistics, 28(3), 710--721
  9. Safo, S., Ahn, J., Jeon, Y. and Jung, S. (2018), Sparse Generalized Eigenvalue Problem for Canonical Correlation Analysis With Application to Integrative Analysis of Methylation and Gene Expression Data, Biometrics, 74(4), 1362--1371.
  10. Jung, S., Lee, M. H., and Ahn, J. (2018), On the number of principal components in high dimensions, Biometrika, 105(2), 389-402.
  11. Kwon, S., Ahn, J., Jang, W., Lee, S., and Kim, Y. (2017), A Double Sparse Penalty Approach for Group Variable Selection, Annals of the Institute of Statistical Mathematics, 69:997-1025.
  12. Park, J. and Ahn, J. (2017), Clustering Multivariate Functional Data with Phase Variation, Biometrics, 73(1), 324-333.
  13. Safo, S. and Ahn, J. (2016), General Sparse Multi-class Linear Discriminant Analysis, Computational Statistics and Data Analysis, 99:81-90.
  14. Ahn, J. and Jeon, Y. (2015), Sparse HDLSS Discrimination with Constrained Data Piling, Computational Statistics and Data Analysis, 90, 74-83.
  15. Jeon, Y., Ahn, J., and Park, C. (2015), A Nonparametric Kernel Approach to Interval-Valued Data Analysis, Technometrics, 57(4):566-575.
  16. Lee, J., Dobbin, K. K., and Ahn, J. (2014), Covariance Adjustment for Batch Effect in Gene Expression Data, Statistics in Medicine, 33(15):2681-2695 .
  17. Lee, M. H., Ahn, J. and Jeon, Y. (2013), HDLSS Discrimination with Adaptive Data Piling, Journal of Computational and Graphical Statistics, 22:433-451.
  18. Ahn, J., Peng, M., Park, C., and Jeon, Y. (2012), A Resampling Approach for Interval-Valued Data Regression, Statistical Analysis and Data Mining, 5, 336-348.
  19. Ahn, J., Lee, M. H., and Yoon, Y. J. (2012), Clustering High Dimension, Low Sample Size Data Using the Maximal Data Piling Distance, Statistica Sinica, 22(2): 443-464.
  20.  Park, C., Ahn, J., Hendry, M.and Jang, W. (2011), Analysis of Long Period Variable Stars with Nonparametric Tests for Trend Detection, Journal of the American Statistical Association, 106(495):832-845.
  21. Ahn, J. (2011), Review of "Principles and Theory for Data Mining and Machine Learning", by Clarke, Fokoue, and, Zhang, Journal of the American Statistical Association, 106(493):375-382.
  22. Park, E., Spiegelman, C. and Ahn, J. (2011), A Nonparametric Approach Based on a Markov like Property for Classification, Chemometrics and Intelligent Laboratory Systems, 108:87-92.
  23. Ahn, J. and Lee, M. H. (2011), Discussion on ``Two-Stage Procedures for High-Dimensional Data" by Makoto Aoshima and Kazuyoshi Yata, Sequential Analysis, 30:423-426.
  24. Park, C., Lazar, N., Ahn, J., and Sornborger, A. (2010), A Multiscale Analysis of the Temporal and Spatial Characteristics of Resting fMRI Data, Journal of Neuroscience Methods, 193:334-342.
  25. Ahn, J. (2010), A Stable Hyperparameter Selection for the Gaussian RBF Kernel for Discrimination, Statistical Analysis and Data Mining, 3(3):142-148.
  26. Ahn, J. and Marron, J. S. (2010), The Maximal Data Piling Direction for Discrimination, Biometrika, 97(1):254-259.
  27. Marron, J. S., Todd, M. J., and Ahn, J. (2007), Distance Weighted Discrimination, Journal of the American Statistical Association, 102(480): 1267- 1271.
  28. Ahn, J., Marron, J. S., Muller, K.E. and Chi, Y. -Y. (2007), The High Dimension, Low Sample Size Geometric Representation Holds Under Mild Conditions, Biometrika, 94(3):760-766.
  29. Liu, Y., Zhang, H. H., Park, C. and Ahn, J. (2007), Support Vector Machines with Adaptive Lq Penalty, Computational Statistics and Data Analysis, 51, 6380-6394.
  30. Zhang, H., Ahn, J., Lin, X., and Park, C. (2006), Gene Selection Using Support Vector Machines with Nonconvex Penalty, Bioinformatics, 22, 88-95.
  31.  Robinson III, W. P., Stiffler, A., Rutherford, E. J., Ahn, J., Hurd, H., Baker, C. C., Meyer, A., and Rich, P. B. (2004), Blood Transfusion is an Independent Predictor of Increased Mortality in Nonoperatively Managed Blunt Hepatic and Splenic Injuries, Journal of Trauma-Injury Infection & Critical Care, 58(3):437 - 445.
  32. Ahn, J. and Park, S. H. (1999), Optimal Restrictions on Regression Parameters For Linear Mixture Model, Journal of Korean Statistical Society, Vol. 28, No. 3, 325 - 336.