JSM Preliminary Online Program
This is the preliminary program for the 2009 Joint Statistical Meetings in Washington, DC.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.


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Legend: = Applied Session, = Theme Session, = Presenter
Washington Convention Center = “CC”, Renaissance Washington, DC Hotel = “RH”

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436 Wed, 8/5/09, 8:30 AM - 10:20 AM CC-Hall D
Contributed Oral Poster Presentations - Contributed - Poster Presentations
Section on Statistical Learning and Data Mining
Chair(s): Lara Schmidt, RAND Corporation
Poster Topic: Statistical Analysis of Text:
37: Statistical Learning of Word Acquisition with Application to Readability PredictionPaul B. Kidwell, Purdue University; Guy Lebanon, Georgia Institute of Technology; Kevyn Collins-Thompson, Microsoft Research
Poster Topic: Data mining and knowledge discovery, machine learning:
38: Performance of Algorithms for Chemometric CalibrationStanislav Zakharkin, Solae; David Ryan, Solae; Nicole Mueth, Solae; Kyoungmi Kim, University of California, Davis
39: Spatial Voxel Co-Occurrence Matrices and Correction Functions for Multiple Magnetic Resonance Imaging ScannersYulan Liang, University of Maryland, Baltimore; Arpad G. Kelemen, University of Maryland, Baltimore
Poster Topic: Bootstrap, resampling methods:
40: AdaBoost from the Perspective of Importance SamplingQingzhao Yu, Louisiana State University Health Sciences Center
Poster Topic: Time series, wavelet analysis, signal processing:
42: Testing Equality of Latent Variables Across GroupsHui Huang, University of Maryland, Baltimore County
Poster Topic: Data mining and knowledge discovery, machine learning:
43: Clustering via Data SpectroscopyJared Schuetter, The Ohio State University; Tao Shi, The Ohio State University
Poster Topic: Business, financial, and marketing statistics:
44: Session-Centric Page Sequence Clustering for Improving Web ExperienceLakshminarayan K. Choudur, Hewlett-Packard Laboratories
Poster Topic: Computational statistics, numerical methods, simulation:
45: Variable Selection for ClusteringHyang Min Lee, Penn State University; Jia Li, Penn State University
Poster Topic: Mathematical statistics, distribution theory, robust statistics:
46: Weighted Distance-Weighted Discrimination and Its Asymptotic PropertiesXingye Qiao, The University of North Carolina at Chapel Hill; Hao (Helen) Zhang, North Carolina State University; Yufeng Liu, The University of North Carolina at Chapel Hill; Michael Jeremy Todd, Cornell University; J. Steve Marron, The University of North Carolina at Chapel Hill
Poster Topic: Applications and case studies:
47: The Application of Periodic Autoregressive Moving Average (PARMA) Model and Seasonal Kendall (SEAKEN) Method in Water-Quality Trend Analysis of Minnesota RiverMohammad L. Rahman, Minnesota State University; Deepak Sanjel, Minnesota State University
Poster Topic: Biometrics, bioinformatics, computational biology:
48: Methods for the Processing of Large-Scale High-Resolution LC/MS DataTianwei Yu, Emory University
Poster Topic: Social and behavioral science:
49: Regression Trees for Group-Randomized TrialsAnne-Michelle Noone, Georgetown University; Rebecca Andridge, University of Michigan
Poster Topic: Mathematical statistics, distribution theory, robust statistics:
50: Outlier Detection in Functional Data AnalysisPallavi Sawant, Auburn University; Nedret Billor, Auburn University
Poster Topic: Computational statistics, numerical methods, simulation:
51: Supervised Dimensionality Reduction on the Fusion of Dissimilarity MatricesZhiliang Ma, Johns Hopkins University; Carey E. Priebe, Johns Hopkins University
Poster Topic: Categorical, multivariate analysis:
54: Clustering Relationships in High-Dimensional DataTimothy Au, Cornell University; Wei Jiang, Hong Kong University of Science and Technology
Poster Topic: Applications and case studies:
55: Power Simulation Using Nonlinear Bayesian Prediction Model on Alcohol Dependence Literature DatabaseYun-Fei Chen, Eli Lilly and Company; Haoda Fu, Eli Lilly and Company
Poster Topic: Experimental design:
56: Planning the Optimal Get-Out-the-Vote Campaign Using Randomized Field ExperimentsAaron Strauss, Princeton University; Kosuke Imai, Princeton University
Poster Topic: Data mining and knowledge discovery, machine learning:
57: A Comparison of Logic Regression and CART for Identifying Important SNP InteractionsWonsuk Yoo, Wayne State School of Medicine; Michele Cote, Karmanos Cancer Institute/Wayne State University; Ann Schwartz, Karmanos Cancer Institute
 

JSM 2009 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised September, 2008