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Course Notes

  1. Tuesday, Jan. 12: STOR893-01-12-2016  – Organizational Matters, What is OODA?, Visualization by Projection, Object Space and Descriptor Space, Curves as Data Objects, Data Representation Issues, PCA Visualization, PCA Terminology, Toy Examples
  2. Thursday, Jan. 14: STOR893-01-14-2016 – Web Page, Toy Example, Spanish Mortality Data, Time Series of Curves, Chemometric Data
  3. Tuesday, Jan. 19: STOR893-01-19-2016 – RNA-seq Data, Linear Algebra Background, Multivariate Probability Background, Limitations of PCA, NCI-60 Data, Matlab Software (Example Script File VisualizeNextGen2011.m, Corresponding Data Set exonsMarron.csv), Marginal Distribution Plots
  4. Thursday, Jan. 21: STOR893-01-21-2016 – Marginal Distribution Plots – Chemometric Data, Transformation, Melanoma Data, Yeast Cell Cycle Data
  5. Tuesday, Jan. 26: STOR893-01-26-2016 – Yeast Cell Cycle Data – Fourier Analysis, Batch Adjustment
  6. Thursday, Jan. 28: STOR893-01-28-2016 – DiProPerm Testing, Chemometric Data, High Dimension Low Sample Size (HDLSS) Asymptotics, Geometric Representation
  7. Tuesday, Feb. 2: STOR893-02-02-2016 –  HDLSS asymptotics, Correlation vs. Independence, Assumptions for Geometric Representation, PCA Consistency
  8. Thursday, Feb. 4: STOR893-02-04-2016 – HDLSS Analysis of DiProPerm, Cornea Data, Robust Statistics, Outliers in PCA
  9. Tuesday, Feb. 9: STOR893-02-09-2016  – Cornea Data, Robust Statistics, Spherical PCA, Elliptical PCA, Big Picture View of PCA, GWAS data
  10. Thursday, Feb. 11: STOR893-02-11-2016 – GWAS data, VL1 PCA for HDLSS Robustness Against Family Effects, PCA History and Background, PCA Mathematics – Anna Zhao: Surviving in the NBA
  11. Tuesday, Feb. 16: STOR893-02-16-2016 – PCA Mathematics, PCA Redistribution of Energy, Correlation PCA, PCA vs, SVD, Different Views, Data Representation  – Wes Crouse: Bayesian Clustering and Data Integration
  12. Thursday, Feb. 18: STOR893-02-18-2016 – Dimension Reduction by PCA, PCA Simulation, Directions for Graphical Displays, Dual PCA, Dual Analysis of Demography Data, Classification / Discrimination, Fisher Linear Discrimination – Sherif Faraq: Rational Design of ED Free Chemicals
  13. Tuesday, Feb. 23: STOR893-02-23-2016 – FLD Nonparametric Derivation, FLD Likelihood Derivation, Mahalanobis Distance, Classical Summary via Toy Examples, HDLSS examples – Jessime Kirk: lncRNA Functional Prediction
  14. Thursday, Feb. 25: STOR893-02-25-2016-part1STOR893-02-25-2016-part2, STOR893-02-25-2016-part3  – HDLSS Discrimination, Maximal Data Piling, Kernel Embedding – Erika Helgeson: Nonparametric Cluster Significance Testing
  15. Tuesday, March 1:  STOR893-03-01-2016 – Kernel Embedding: Naive Explicit and Implicit, Radial Basis Functions, Support Vector Machines
  16. Thursday, March 3: STOR893-03-03-2016-part1STOR893-03-03-2016-part2 – Distance Weighted Discrimination,DWD & Face Data, DWD Simulations, DWD Batch Adjustment, SVM & DWD Tuning – Frank Teets: Characterizing Protein Assembly Graphs
  17. Tuesday, March 8: STOR893-03-08-2016-part1STOR893-03-08-2016-part2 – Radial DWD & Virus Hunting, Melanoma Data & ROC Curves, Clusters in Mass Flux Data, Statistical Smoothing (Density & Regression Estimation)
  18. Thursday, March 10: STOR893-03-10-2016-part1STOR893-03-10-2016-part2 – Smoothing Bandwidth Selection, Scale Space, SiZer, Revisit Cell cycle Data, Clustering, K-means – Jasmine Yang:  OODA of PNC Data
  19. Tuesday, March 15: No Class – Spring Break
  20. Thursday, March 17: No Class – Spring Break
  21. Tuesday, March 22: – STOR893-03-22-2016-QingFeng-Trans – Qing Feng – Automatic Transformations
  22. Thursday, March 24: – STOR893-03-24-2016-QingFeng-JIVE – Qing Feng – JIVE
  23. Tuesday, March 29: STOR893-03-29-2016 – Clustering, K-Means, SWISS Score, Hierarchical Clustering – Xiao Yang: Analysis of Climate Data, Huijun Qian: Quantitative Analysis of Non-muscle Myosin II Minifilaments
  24. Thursday, March 31: STOR893-03-31-2016 – SigClust, QQ envelope plots, Shape statistics – Rui Wang
  25. Tuesday, April 5: – STOR893-04-05-2016-HyowonAn – Hyowon An – L-Statistics
  26. Thursday, April 7: – STOR983-04-07-2016-QunqunYu-part1, STOR983-04-07-2016-QunqunYu-part2STOR983-04-07-2016-QunqunYu-part3 – Qunqun Yu – OODA of Brain Imaging Data
  27. Tuesday, April 12: – STOR893-04-12-2016 – SigClust & Genetic Examples, Shapes as Data Objects, Landmark Based Shape, Equivalence Relations, Quotient Space – Muyong Wang: OODA of Human Microbiome Data, Hanyan Wang: Tissue MicroArray Data, Ruituo Fan: Functional Additive Regression
  28. Thursday, April 14: – STOR893-04-14-2016 – Manifold Descriptor Space, OODA in Image Analysis, Shape Representations – Nuvan Rathnayaka: Semi-Supervised Clustering, Leo Yufeng Liu: Image Oriented Data Analysis: Spatial Regularized Image Classification, Yichen Tu: PCA document reconstruction for email classification
  29. Tuesday, April 19: – STOR893-04-19-2016 – Medial Shape Representations, Bladder-Prostate-Rectum Data, Composite Prinicpal Nested Spheres – Mahmoud Mostapha: Fast Editing of Many Object Segmentation, Megan Quinn ; Smoothing in Human Growth Data
  30. Thursday, April 21: – STOR893-04-21-2016 – Backwards PCA, Nonnegative Matrix Factorization, Principal Curves, Topics not Covered: ICA, Trees, Purely Metric analysis (MDS) – Heejoon Jo: Clustering using RNAseq and Junction Information, Whitney Zheng: Device usage anomaly detection using Time Series, Iain Carmichael: Connections between SVM and other linear classifiers
  31. Tuesday, April 26:  No Class – Marron Out of Town


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Godtliebsen, F., Marron, J. S., & Chaudhuri, P. (2004). Statistical significance of features in digital images. Image and Vision Computing, 22(13), 1093-1104 (cited 3/10/16)

Godtliebsen, F., Marron, J. S., & Pizer, S. M. (2002). Significance in scale-space for clustering. Spatial clustering modeling. Chapman and Hall/CRC, 24-36 (cited 3/10/16)

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Wang, B., & Zou, H. (2015). Sparse distance weighted discrimination. Journal of Computational and Graphical Statistics, (just-accepted), 00-00 (cited 3/1/16)

Wang, H. and Marron, J. S. (2007) Object oriented data analysis: sets of trees, Annals of Statistics, 35, 1849-1873  (cited 1/12/16)

Wei, S., Lee, C., Wichers, L., & Marron, J. S. (2015). Direction-projection-permutation for high dimensional hypothesis tests. Journal of Computational and Graphical Statistics, (cited 1/26/16, 2/2/16)

Wright, F. A., Strug, L. J., Doshi, V. K., Commander, C. W., Blackman, S. M., Sun, L., … & Corey, M. (2011). Genome-wide association and linkage identify modifier loci of lung disease severity in cystic fibrosis at 11p13 and 20q13. 2. Nature genetics, 43(6), 539-546 (cited 2/4/16)

Xiong, J., Dittmer, D. P., & Marron, J. S. (2015). “Virus hunting” using radial distance weighted discrimination. The Annals of Applied Statistics, 9(4), 2090-2109 (cited 3/3/16)

Yata, K., & Aoshima, M. (2009). PCA consistency for non-Gaussian data in high dimension, low sample size context. Communications in Statistics—Theory and Methods, 38(16-17), 2634-2652 (cited 2/2/16)

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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 4/14/16)

Zhang, L., Marron, J. S., Shen, H., & Zhu, Z. (2007). Singular value decomposition and its visualization. Journal of Computational and Graphical Statistics, 16(4), 833-854 (cited 2/16/16)

Zhang, L., Lu, S., & Marron, J. S. (2015). Nested nonnegative cone analysis. Computational Statistics & Data Analysis, 88, 100-110 (cited 4/21/16)

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Marron’s OODA Matlab Software

 Overview Page

.zip File With All

Download into 4 directories, and put each in Matlab path


Course Information

Class Meetings:

Tuesday – Thursday 9:30 – 10:45,   Hanes Hall 125


Steve Marron, Professor



Hanes Hall 352    (in back hall behind central open area on 3rd floor)


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)