Shanshan Ding, Ph.D.
Ph.D., Statistics, University of Minnesota, Minneapolis, 2014
M.S., Applied and Computational Mathematics, University of Minnesota, Duluth, 2008
M.S., Finance, Peking University, 2004
B.S., Applied Mathematics, Nankai University, 2002
STAT 617-010 – Multivariate Methods
Dimension reduction, high dimensional data analysis, multivariate analysis, envelope models, imaging data analysis, longitudinal data analysis, econometrics, health and environmental applications.
Ding, S. and Cook, R. D. (2015). Tensor sliced inverse regression. Journal of Multivariate Analysis, 133, 216–231.
Ding, S. and Cook, R. D. (2014). Dimension folding PCA and PFC for matrix-valued predictors. Statistica Sinica, 24, 463-492.
Ding, S. and Sinha, M. (2011). Evaluation of power of diferent Cox proportional hazards models incorporating stratification factors. In JSM Proceedings. Miami, FL: American Statistical Association, pp. 4307-4320.
Ding, S. and Cook, R. D. (2014). Matrix-variate regressions and the envelope models. Preprint.
Ding, S. and Cook, R. D. (2014). Higher-order sliced inverse regression. Preprint.