Events
JSM 2007
Statistical Computing and Statistical Graphics Paper Competition
Topic contributed papers
- Improved Centroids Estimation for the Nearest Shrunken Centroid Classifier – Sijian Wang, University of Michigan; Ji Zhu, University of Michigan
- Exploratory Model Analysis with R and GGobi – Hadley Wickham, Iowa State University
- spBayes: An R Package for Univariate and Multivariate Hierarchical Point-Referenced Spatial Models – Andrew Finley, The University of Minnesota; Sudipto Banerjee, The University of Minnesota; Brad Carlin, The University of Minnesota
- A Flexible Variable Selection Algorithm for the Cox Model with High-Dimensional Data – Alexander Pearson, University of Rochester; Derick R. Peterson, University of Rochester
Exploring Models Interactively
Invited papers
- Bayesian Information Analysis – Aleks Jakulin, Columbia University; Andrew Gelman, Columbia University
- Exploratory Model Analysis: Interactive Graphical Methods for Model Selection and Comparison – Simon Urbanek, AT&T Labs - Research
- Grammatical Visualization of Statistical Models – Graham Wills, SPSS Inc.; Chunling Zhang, SPSS Inc.
- Exploring Models for Clustering Data – Dianne Cook, Iowa State University
Applications of Visualization for Web 2.0
Topic contributed papers
- An AJAX Web 2.0 Geospatial Visualization Framework – Stephen Eick, University of Illinois at Chicago
- Statistical Graphics with Element Control in the Browser – Sven Knudsen and Stephen Kaluzny, Michael O'Connell
- Using Web 2.0 for Statistical Software – Webster West, Texas A&M University
- Statistical Graphics for Collaborative Environments – Daniel Rope, SPSS Inc.
Statistical Graphics for Everyday Use?
Panel
- John Emerson, Yale University
- Frederick Wicklin, SAS Institute Inc.
- Leland Wilkinson, SPSS Inc.
Scagnostics
Invited - Papers
- Scagnostics in R – Hadley Wickham, Iowa State University; Duncan Temple Lang, University of California, Davis
- Scagnostic-Driven Autovisualization – Graham Wills, SPSS Inc.
- Scagnostics for Projection Pursuit – Heike Hofmann, Iowa State University; Dianne Cook, Iowa State University; Hadley Wickham, Iowa State University
Statistical Methods for Graphs and Networks
Topic Contributed - Papers
- Bayesian Self-Modeling Warping Regression – Donatello Telesca, University of Washington; Lurdes Inoue, University of Washington
- What Is a 'Random Network'? – David Hunter, The Pennsylvania State University
- Collective Inference for Network-Based Marketing – Shawndra Hill, University of Pennsylvania
- Transitivity in Weighted Graphs: Effects on the Topology of Knowledge and Social Networks – Tiago Simas, Indiana University; Bharat Dravid, Indiana University; Luis Rocha, Indiana University
Statistical Graphics for Analysis of Drug Safety and Efficacy
Topic Contributed - Papers
- Statistical and Graphical Analysis of Adverse Event Counts in Clinical Trials – Michael O'Connell, Insightful Corporation
- Using Graphics To Discover and Explore – Julia Wang, Johnson & Johnson PRD
- Understanding Clinical Trial Data Through Use of Statistical Graphics – Will Bushnell , GlaxoSmithKline
- Graphical Analyses of Clinical Trial Safety Data – Haijun Ma, Amgen Inc.; Kefei Zhou, Amgen Inc.; Hong A. Xia, Amgen Inc.; Matthew Austin, Amgen Inc.; George Li, Amgen Inc.; Michael O'Connell, Insightful Corporation
- Design of Statistical Graphics for Clinical Data – Richard M. Heiberger, Temple University
Statistical Graphics - Methods and Applications
Contributed - Papers
- Visualizing Cluster-Compressed Multivariable and Multialtitude Atmospheric Data – Daniel Carr, George Mason University; Amy Braverman, Jet Propulsion Laboratory
- An Exploratory Stroll Along the Beach – Charlotte Wickham, University of California, Berkeley
- Characterizing Multivariate Data with High-Resolution Human Faces – Dean Nelson, University of Pittsburgh at Greensburg; Joe Szurek, University of Pittsburgh at Greensburg
- Graphs in Social Science Texts: We Can and Should Do Better – Naomi Robbins, NBR-Graphs; Joyce Robbins, Touro College
- Longitudinal Multivariate Graphics in the Analysis of Time Management Data – Jessica M. Scott, Brigham Young University; Steven A. Wygant, Brigham Young University; Bruce Brown, Brigham Young University
- Generating Data with Identical Statistics but Dissimilar Graphics: A Follow-Up to the Anscombe Dataset – Sangit Chatterjee, Northeastern University; Firat Aikut, Northeastern University
- A Note on the Barnett-Cohen Censored Histogram – Jong Kim, Portland State University; Bryan G. Schar, U.S. Census Bureau
Some New Developments in Statistical Learning
Invited - Papers
- The Adaptive Lasso and Its Oracle Properties – Hui Zou, The University of Minnesota
- Robust Support Vector Machines – Yufeng Liu, The University of North Carolina at Chapel Hill
- Bayesian Ensemble Active Learning – Hugh Chipman, Acadia University; Edward I. George, University of Pennsylvania; Robert McCulloch, The University of Chicago Graduate School of Business
Hardware, Software, and Algorithms
Contributed - Papers
- WISDOM for µStat: Web-Based Support for the Analysis of Multivariate Hierarchical Data – Knut M. Wittkowski, The Rockefeller University
- Creating Statistical Web Services Using ASP.NET – Neil Polhemus, StatPoint, Inc.
- Grid Computing – Abdullah Alnoshan, George Washington University; Shmuel Rotenstreich, George Washington University; Adil Rajput, BearingPoint
- Access Control Model for E-Learning System – Fahad Bin Muhaya, Imam University; Yasmin H. Said, George Mason University
- A Web-Based Program for Computing Percentage Points of Pearson Distributions – Wei Pan, University of Cincinnati; Haiyan Bai, University of Central Florida; Shengbao Chen, JMW Truss & Components
- minSpline: An R Package for Fitting Splines – Sundar Dorai-Raj, PDF Solutions, Inc.; Spencer Graves, PDF Solutions, Inc.
- Calculating the Interatomic Distance Distribution from Small-Angle X-Ray Scattering via Curve Averaging – Lanqing Hua, Purdue University; Alan Friedman, Purdue University; Chris Bailey-Kellogg, Dartmouth University; Bruce Craig, Purdue University
Symbolic, Time Series, and Image Analysis
Contributed - Papers
- Exact Properties of a New Test and Other Tests – Jie Peng, University of Louisiana at Lafayette; Kalimuthu Krishnamoorthy, University of Louisiana at Lafayette
- On a Moment-Based Test for Normality – Yihao Deng, Indiana University Purdue University Fort Wayne; Chand Chauhan, Indiana University Purdue University Fort Wayne
- Testing of Hypothesis of a Structured Mean Vector for Multilevel Multivariate Data with Structured Correlations on Repeated Measurements – Anuradha Roy, The University of Texas at San Antonio; Ricardo Leiva, F.C.E. Universidad Nacional de Cuyo
- Resampling-Based Multiple Testing Procedure – Nasrine Bendjilali, Lehigh University; Wei-Min Huang, Lehigh University
- On an Efficient Algorithm for Boundary Detection – Tsung-Lin Cheng, National Changhua University of Education
- A Geometric Feasible Direction Algorithm for Large-Scale Optimization with l1 Norm Constraint – Jian Zhang, Purdue University
- Impact of Censoring on Inference for the Regression Coefficient in a Bivariate Normal Model – Richard Linder, Ohio Wesleyan University
- Symbolic Data Analysis – Lynne Billard, University of Georgia
- Temporal Statistics for Consequences of Alcohol Use – Peter Mburu, George Mason University; Yasmin H. Said, George Mason University; Edward Wegman, George Mason University
- Time-Frequency Analysis of Electroencephalogram Series – Wei Yang, SUNY at Albany; Stephen Wong, University of Pennsylvania; Igor Zurbenko, SUNY at Albany
- Temporal Extensions to Spatial Statistical Metrics – James Shine, U.S. Army Topographic Engineering Center; James P. Rogers, U.S. Army Corps of Engineers; Mete Celik, The University of Minnesota; Shashi Shekhar, The University of Minnesota
- Approaches to Time Series Clustering – Hwanseok Choi, The University of Alabama; J. Michael Hardin, The University of Alabama
- An Empirical Spectral Test (EST) for Random Sequences – David Zeitler, Grand Valley State University; Joseph W. McKean, Western Michigan University; John Kapenga, Western Michigan University
- Using Geometrical Tools for Dimension Reduction of Images – Evgenia Rubinshtein, University of Central Arkansas; Anuj Srivastata, Florida State University
Large Scale Data Mining
Invited - Papers
- A New Family of Link Functions Extending Logistic Regression – William DuMouchel, Lincoln Technologies
- Statistics and Search Engines – Daryl Pregibon, Google
- A Poor Man's View of Data Mining – William F. Szewczyk, National Security Agency
Mixture Models and Expectation Maximization
Contributed - Papers
- Nonparametric Transformation of the Data to Obtain Bias Reduction in Kernel Estimation of the Distribution Function of Nonstandard Mixtures – Ennis McCune, Stephen F. Austin State University; Sandra L. McCune, Stephen F. Austin State University
- Fitting Mixture Distributions Using Generalized Lambda Distributions (GLDs): Examples, Comparisons with Normal Mixtures, and Computational Considerations – Wei Ning, Bowling Green State University; E. J. Dudewicz, Syracuse University
- Acceleration of the EM Reconstruction Algorithm for PET Images Using Squared Iterative Methods – Constantine E. Frangakis, Johns Hopkins University; Ravi Varadhan, Johns Hopkins University; Christophe Roland, University of Science and Technology at Lille
- Improving the Efficiency of the Monte Carlo EM Algorithm Using Squared Iterative Methods – Ravi Varadhan, Johns Hopkins University; Brian S. Caffo, Johns Hopkins Bloomberg School of Public Health; Wolfgang Jank, University of Maryland
- Generalized t-Copula and Its Application on Biometric – Wenmei Huang, Michigan State University; Sarat Dass, Michigan State University
- Comparison of the Six Sigma and Lean Sigma on the IT Management Processes – Genady Grabarnik, IBM T.J. Watson Research Center; Larisa Shwartz, IBM T.J. Watson Research Center
Machine Learning
Contributed - Papers
- Semisupervised Learning from Dissimilarity Data – Michael Trosset, Indiana University; Carey E. Priebe, Johns Hopkins University
- Algorithms for Support Vector Machines – Denise Reeves, George Mason University
- Random Forests for Feature Selection: To Be Handled with Caution – Carolin Strobl, LMU Munich
- Feature Selection for Large Data – Peng Liu, Case Western Reserve University; Jiayang Sun, Case Western Reserve University
- Asymptotic Mean Squared Prediction Error of L2Boosting Estimator Under Mis-specified Models – Tzu-Chang Cheng, University of Illinois at Urbana-Champaign; Ching-Kang Ing, Academia Sinica
- On Efficient Supervised Learning of Multivariate t Mixture Models with Missing Information – Tsung-I Lin, National Chung Hsing University; Hsiu-J Ho, National Chung Hsing University; Pao-S Shen, Tunghai University
- Conditional Confidence Intervals for Classification Error Rate – Hie-Choon Chung, Gwangju University; Chien-Pai Han, University of Texas at Arlington
Computationally Intensive Methods
Invited - Papers
- Exploratory Statistical Software – Antony Unwin, University of Augsburg
- Reducing the Variability in Least Squares Cross-Validation Bandwidths – Jeffrey Hart, Texas A&M University; Simon Sheather, Texas A&M University
- K Models Clustering – James E. Gentle, George Mason University; Li Li, George Mason University