Course Home Page – STOR 892 – OODA – Marron

Class Notes:

  1. Tuesday, August 19, 2014 – STOR892-8-19-2014  – Organizational Matters – What is OODA? – Visualization by Projection – Object Space and Descriptor Space – Curves as Data Objects – Data Representation Issues – PCA Visualization – PCA Terminology
  2. Thursday, August 21, 2014 – STOR892-8-21-2014 – Mortality Data Time Series of Curves & Color Coding – Chemo-metric Data – Glioblastoma Data & Brushing – Limitations of PCA – NCI 60 Data – Directions Beyond PCA
  3. Tuesday, August 26, 2014 – STOR892-8-26-2014 – Directions Beyond PCA, Fourier Basis Directions, Gene Cell Cycle Data Analysis, DWD, Batch Adjustment
  4. Thursday, August 28, 2014 – STOR892-8-28-2014 – Matlab Software (Example Script File: VisualizeNextGen2011.m), Cornea Data, Robustness, Spherical PCA
  5. Tuesday, September 2, 2014 – STOR892-9-02-2014 – Elliptical PCA & Cornea Data, Big Picture PCA, Correlation PCA, Melanoma Data, Transformations, Marginal Distribution Plot, Clusters
  6. Thursday, September 4, 2014 – STOR892-9-04-2014-part1 – STOR892-9-04-2014-part2 – Smoothing: Density and Regression Estimation, Hidalgo Stamp Data, Kernel Density Estimation, Fossils Data, Local Linear Smoothing, SiZer, Data Examples: Internet, British Family Incomes, Yeast Cell Cycle
  7. Tuesday, September 9, 2014 – OODA-JieXiong – Jie Xiong: Radial Distance Weighted Discrimination
  8. Thursday, September 11, 2014 – STOR892-9-11-2014 – Finish Mass Flux & Cell Cycle Data, Big Picture PCA, Linear Algebra Review
  9. Tuesday, September 16, 2014 – STOR892-9-16-2014 – Continue Review of Linear Algebra, Eigen-analysis solution of Matrix problems, Multivariate Probability Review, PCA as Optimization, Connect Math to Graphics, PCA Redistribution of Energy,
  10. Thursday, September 18, 2014 – STOR892-9-18-2014 – PCA Data Representation & Simulation, Alternate PCA Calculation, Dual PCA, Classification / Discrimination
  11. Tuesday, September 23, 2014 – STOR892-9-23-2014-part1, STOR892-9-23-2014-part2  – Fisher Linear Discrimination (Intuitive & Likelihood Derivation), Gaussian Likelihood Ratio, Principal Discriminant Analysis, HDLSS Discrimination, Maximal Data Piling
  12. Thursday, September 25, 2014 – STOR892-9-25-2014-JIVE-QingFeng – Qing Feng – Joint and Individual Variation Explained
  13. Tuesday, September 30, 2014 – STOR892-9-30-2014-CSPCA-DiMiao – Di Miao – Class Sensitive PCA
  14. Thursday, October 2, 2014 – Patrick Kimes – Sig-Clust & Sig Fuge
  15. Tuesday, October 7, 2014 – STOR892-10-07-2014-Part1 STOR892-10-07-2014-part2 STOR892-10-07-2014-part3 – Maximal Data Piling, Kernel Embedding –  PP:  John Palowitch {Network Statistics}, Eduardo Garcia {KDE for Spherical data}
  16. Thursday, October 9, 2014 – STOR892-10-09-2014 – Kernel Embedding, Support Vector Machine –  PP: Guan Yu {Sparse regression & Graphical Structure}
  17. Tuesday, October 14, 2014 – STOR892-10-14-2014  – Support Vector Machine, Distance Weighted Discrimination –  PP: Hyowon An {Finding MLE of normal mixture models}, Robert Corty {Modeling population structure — from PCA to mixed models}
  18. Thursday, October 16, 2014 – No Class, Fall Break
  19. Tuesday, October 21, 2014 – STOR892-10-21-2014-part1 – STOR892-10-21-2014-part2 – HDLSS Discrimination Simulations, Batch Adjustment, Melanoma Data, ROC curves, Clustering – PP: Qunqun Yu {Curve Registration}
  20. Thursday, October 23, 2014 – STOR892-10-23-2014 – Hierarchical Clustering, SigClust, DiProPerm – PP: Qingyu Zhao {Data-Driven Thin Shell Deformation}, Suman Chakraborty {RandomMatrices}
  21. Tuesday, October 28, 2014 – STOR892-10-28-2014 – SigClust, QQ plots  – PP: True Price {FMRI Network Segmentation}
  22. Thursday, October 30, 2014 – STOR892-10-30-2014 – SigClust, Start HDLSS Asymptotics –  PP:  Qing Duan {Admixtures in GWAS}
  23. Tuesday, November 4, 2014 – STOR892-11-04-2014 – HDLSS Asymptotics
  24. Thursday, November 6, 2014 – STOR892-11-06-2014 – Finish HDLSS Asymptotics, Independent Component Analysis – PP: JP Hong {Shape Classification}
  25. Tuesday, November 11, 2014 – STOR892-11-11-2014 – Independent Component Analysis, HDLSS & MDLSS, Shapes as Data Objects, Equivalence Relations & Classes – PP: Natalie Stanley {Parameter Estimation in Multilayer Stochastic Block Models}
  26. Thursday, November 13, 2014 – STOR892-11-13-2014-part1STOR892-11-13-2014-part2 – Shape Representations, Manifold Data, Directional Data, Manifold Versions of PCA –  PP: Sai Balu {Identifying APOBEC Mutation Signatures on Breast Cancer Samples}
  27. Tuesday, November 18, 2014 – STOR892-11-18-2014-part1STOR892-11-18-2014-part2 – Principal Nested Spheres, Backwards PCA, Nonnegative Matrix Factorization – PP: Meilei Jiang {OODA for Microbiomes}
  28. Thursday, November 20, 2014 – STOR892-11-20-2014 – Nonnegative Nested Cone Analysis, Curve Registration – PP: Siliang Gong {Variable Selection for Ultra-High Dimensional Data}, Yang Yu {ADNI Data}
  29. Tuesday, November 25, 2014 – STOR892-11-25-2014  – Fisher Rao Approach to Curve Registration, Proteomics Data  – PP: Hyo Young Choi {NMF analysis of Genetic Sequence Data}, PP: Leo Yufeng Liu {Machine Learning}
  30. Thursday, November 26, 2014 – No Class, Thanksgiving
  31. Tuesday, December 2, 2014 – STOR892-12-02-2014PP: Rasmus Skov Knudsen {L1 PCA}, Micheal Deakin {???}



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  • Staudte, R. G. and Sheather, S. J. (1990) Robust Estimation and Testing, Wiley, New York (cited 8/28/14)
  • Tenenbaum, J. B., de Silva, V. and Langford, J. (2000) A global geometric framework for nonlinear dimensionality reduction. Science, 290, 2319-2322 (cited 11/18/14)
  • Vapnik, V, N. (1982) Estimation of dependences based on empirical data, Springer (Russian version, 1979) (cited 10/9/14)
  • Vapnik, V. N. (1995) The nature of statistical learning theory, Springer (cited 10/9/14)
  • Wand, M. P. & Jones, M. C. (1994) Kernel Smoothing, Chapman & Hall/CRC, ISBN: 0412552701  (cited 9/4/14)
  • Wang, H. and Marron, J. S. (2007) Object oriented data analysis: sets of trees, Annals of Statistics, 35, 1849-1873  (cited 8/19/14, 12/02/14)
  • Wang, Y., Marron, J. S., Aydin, B., Ladha, A., Bullitt, E., & Wang, H. (2012). A nonparametric regression model with tree-structured response. Journal of the American Statistical Association, 107(500), 1272-1285 (cited 12/02/14)
  • Wei, S., Lee, C., Wichers, L., Li, G., and Marron, J.S. (2013) Direction-projection-permutation for high dimensional hypothesis tests, arXiv preprint arXiv:1304.0796 (cited 10/23/14)
  • Yata, K., & Aoshima, M. (2010). Effective PCA for high-dimension, low-sample-size data with singular value decomposition of cross data matrix. Journal of multivariate analysis, 101(9), 2060-2077 (cited 11/11/14)
  • Yata, K., & Aoshima, M. (2012). Effective PCA for high-dimension, low-sample-size data with noise reduction via geometric representations. Journal of multivariate analysis, 105(1), 193-215 (cited 10/30/14)
  • Yushkevich, P., Pizer, S. M., Joshi, S., and Marron, J. S. (2001) Intiutive, localized analysis of shape variability, Information Processing in Medical Imaging (IPMI), eds. Insana, M. F. and Leahy, R. M. 402-408 (cited 11/13/14)
  • Zhang, L., Marron, J. S., & Lu, S. (2013). Nested Nonnegative Cone Analysis. arXiv preprint arXiv:1308.4206 (cited 11/18/14)
  • Zhao, X., Marron, J.S. and Wells, M.T. (2004) The Functional Data View of Longitudinal Data, Statistica Sinica, 14, 789-808 (cited 8/26/14, 9/11/14)


Course Information:

Class Meetings:

Tuesday – Thursday 12:30 – 1:45,   Hanes Hall 125


J. S. Marron, Professor



Hanes Hall 352    (in back hall behind central open area)


Office:    919-962-2188
Home:    919-493-2844

Office hours:

When I am in my office (usually M, T, Th, priority to those with appointments)