Statistics, especially Nonparametric and Robust Multivariate Analysis
Applications of Depth Functions
Data Mining, Outlier Identification and Cluster Analysis
Correlated Data Analysis
Robust Clustering in High Dimensional Data Using Statistical Depths.
BMC Bioinformatics 2007, 8 (Suppl 7)
(with Y. Ding, H. Peng and D. Wilkins). (Open access online)
Depth-Based Novelty Detection and its Application to Taxonomic Research. The Seventh IEEE International
Conference on Data Mining (ICDM), 113-122, Omaha, Nebraska, October 2007
(with Y. Chen, H. Bart and H. Peng). (pdf)
Influence Functions of Some Depth Functions, with Application to L-Statistics. Journal of Nonparametric Statistics, 21 (01), 49-66, 2009 (with R. Serfling and W. Zhou).
Outlier Detection with the Kernelized Spatial Depth Function. IEEE Transactions on Pattern Analysis and Machine
Intelligence, 31(2), 288-305, 2009 (With Y. Chen, H. Peng and H. Bart). (pdf)
A Unified Approach for Analyzing Exchangeable Binary Data
with Applications to Developmental Toxicity Studies. Statistics in Medicine, 28, 2580-2604, 2009 (with S. Keeton and H. Peng). (pdf)(code)
Graph Ranking for Exploratary Gene Data Analysis. BMC Bioinformatics 2009, 10 (Suppl 11)
(with C. Gao, Y. Chen and D. Wilkins). (Open access online)
Nonparametric Depth-Based Multivariate Outlier Identifiers, and Masking Robustness Properties. Journal of Statistical Inference and Planning, 140, 198-213, 2010
(with Robert Serfling). (pdf)
Projection Based Scatter Depth Functions and Associated Scatter Estimators. Journal of Multivariate Analysis, 101, 138-153, 2010
(with Weihua Zhou). (pdf)
The Distribution of Partially Exchangeable Random variables. Statistics and Probability Letters, 80, 932-938, 2010 (with H. Peng and X. Wang).
Learning to Rank Using 1-norm Regularization and Convex Hull Reduction, Proceedings of ACM Southeast Conference (ACMSE), April, 2010 (with X. Nan, Y. Chen and D. Wilkins).
A Numerical Study of Multiple Imputation Methods Using Nonparametric Multivariate Outlier Identifiers and Depth-Based Performance Criteria with Clinical Laboratory Data.
Journal of Statistical Computation and Simulation, 81, 547-560, 2011
(with Robert Serfling). (pdf)
Multiclass Classification with Potential Function Rules:
Margin Distribution and Generalization. Pattern Recognition, 45(1), 540-551, 2012 (with F. Teng, Y. Chen).
The Prediction for Listed
Companies' Financial Distress by Using
Multiple Prediction Methods with Rough
Set and Dempster-Shafer Evidence Theory,
Knowledge-Based Systems , 26, 196-206, 2012 (with Z. Xiao , X. Yang, Y. Pang).
Robust Finite Mixture Learning and its Application to Taxonomic Research,
Research Notes in Information Science , 14, 67-77, 2013 (with K. Yu, H. Bart Jr. and Y. Chen).
Financial Ratio Selection for Business Failure Prediction using Soft Set Theory,
Knowledge Based Systems, 63, 59-67, 2014 (with W. Xu, Z. Xiao).
Accurate and Interpretable Models Based on Regularized Random Forests Regression,
Systems Biology, 8 (Suppl 3), S5, 2014 (with S. Liu, Y. Chen, D. Wilkins).
Robustness of the Affine Equivariant Scatter Estimator Based on the Spatial Rank Covariance
Matrix, Communications in Statistics --Theory and Methods, 44, 914-932, 2015 (with K. Yu, Y. Chen).
Gini Covariance Matrix and its Affine Equivariance Version. Statistical Papers, 60 (3), 291-316, 2019 (with H. Sang, L. Weatherall).
The full-text view-only paper is available at (DOI: 10.1007/s00362-016-0842-z)
Improving the Power of the Diebold-Mariano-West
Test for Least Squares Predictions. International Journal of Forecasting, 33, 618-626, 2017 (with W. Mayer, F. Liu).
Robust and Efficient Boosting Method Using the Conditional Risk. IEEE Transactions on Neural Networks and Learning Systems, 29 (7), 3069-3083,
2018 (with Z. Xiao, Z. Luo and B. Zhong).
Pareto Cascade Modeling of Diffusion
Networks. International Joint Conference on Neural Networks , July 8- 13, 2018, Rio de
Janeiro, Brazil.(with C. Ma, Y. Chen and D. Wilkins) (pdf)
A Rank-based Cramer-von-Mises-type Test for Two
Samples. Brazilian Journal of Probability and Statistics, 33 (3), 425-454, 2019 (with J. Curry, H. Sang).
Jackknife Empirical Likelihood Methods for Gini Correlations, Journal of Statistical Planning and Inference,
199, 45-59, 2019 (with Y. Sang, Y. Zhao).
On Mutual Information Estimation for Mixed-Pair Random Variables, Statistics & Probability Letters, 148, 9-16, 2019 (with A. Beknazaryan, H. Sang).
Weighted Jackknife Empirical Likelihood for Non-smooth U-structure Equations, Test, accepted. (with Y. Sang, Y. Zhao). The full-text view-only paper is available at
Empirical Likelihood Test for Diagonal Symmetry, Statistics & Probability Letters, accepted. (with Y. Sang).
Estimating Feature - Label Dependence using Gini Distance Statistics, IEEE Transactions on Pattern Analysis and Machine Intelligence
, accepted. (with S. Zhang, D. Nguyen, D. Wilkins and Y. Chen). (pdf)
CoPI, "Theil-Sen Estimators in Semiparametric Mixed Models", National Science Foundation, DMS-0707074, 2007-2009
PI, REU supplemental project, National Science Foundation, DMS-0809018, 2008-2009
Former and Current Doctoral Students
Cuilan Gao, Graph Ranking with the Kernelized Spatial Depth and Its Applications, May 2010
(Associate Professor, Department of Mathematics, University of Tennessee at Chattanooga)
Kai Yu, Robust Methods Based on Spatial Rank Functions, December 2012
(Business Intelligence Manager, Amazon Web Service, Amazon)
Jamye Curry, Rank-based Two Sample Tests Under a
General Alternative, August 2014
(Assistant Professor, School of Science and Technology, Georgia Gwinnett College)
Lauren Weatherall, Gini Covariance Matrix and its Affine Equivariant Version, May 2015
(Health Data Analyst, Blue Cross and Blue Shield of Mississippi)
Courtney Vanderford, tentative dissertation: Efficient and Symmetric Gini Correlations.
Robust Statistics (Math776), Spring 15
Data Analysis with R (Math776), Spring 11, Fall 16
Bayesian Statistics (Math775), Fall 10, Fall 12, Spring 17
Statistical Learning I (Math775), Fall 08, Fall 18
Statistical Learning II (Math776), Spring 09. Spring 19
Statistical Methods I (Math675), Fall 11, Fall 13
Statistical Methods II (Math676), Spring 12, Spring 14
Mathematical Statistics I (Math575), Fall 05, 06, 07, 09, 11, 17, 19
Mathematical Statistics II (Math576), Spring 06, 07, 08, 10, 20
Introduction to Acturarial Science (Math480), Fall 07, Fall 08, Spring 16, Spring 17
Introduction to Linear Algebra (Math319), Spring 08
Introduction to Statistics (Math375), Summer 07, Spring 09 - 15, Fall 13 - 15
Calculus III (Math263), Fall 05, Spring 06, Fall 06, Fall 10, Fall 17
Calculus II (Math262), Fall 14, Fall 15, Spring 20
Calculus I (Math261), Summer 09
Elementary Statistics (Math115), Winter 14, Aug 15, Fall 09, 16, 17, 18, 19, Spring 17, 18, 19