PROGRAM

SEVENTH PURDUE

INTERNATIONAL SYMPOSIUM ON STATISTICS

STATISTICAL DECISION THEORY CONFERENCE

JUNE 19-24, 2003

PURDUE UNIVERSITY

WEST LAFAYETTE, INDIANA

THURSDAY, JUNE 19

Registration, Stewart Center – East Foyer, 7:30 a.m. – 5:00 p.m.

8:00 – 12:00 p.m. Pre-Symposium Microarray Tutorial, STEW – Room 202

Instructors: R.W. Doerge and Bruce Craig, Purdue University

1:30 – 3:00 p.m. Workshop A Session 1, STEW – Room 202

Chair: R.W. Doerge, Purdue University

1:30-1:40 p.m. WELCOME

Mary Ellen Bock, Head, Department of Statistics, Purdue University

1:40-2:10 p.m. Rob Williams, University of Tennessee Health Science Center

“Complex Trait Analysis of Array Data: Some Practical and Theoretical

Challenges of Effective Network Analysis”

2:15-2:45 p.m. Katerina Kechris, University of California, Berkeley

"Detecting DNA Regulatory Motifs by Incorporating Positional Trends in

Information Content"

2:45-3:00 p.m. Kerry Bemis, Eli Lilly and Company

“Linear Predictive Methods for Biomarkers using Affymetrix GeneChips”

3:00 – 3:30 p.m. Coffee Break

3:30 – 5:30 p.m. Workshop A Session 2, STEW – Room 202

Chair: Bruce Craig, Purdue University

3:30 - 4:00 p.m. Michael A. Black, University of Auckland, New Zealand

“Multiple Comparisons for Microarray Experiments - Motivation and

Methods”

4:00-4:30 p.m. Sunduz Keles, University of California, Berkeley

“Supervised Detection of Regulatory Motifs in DNA Sequences”

4:30-5:00 p.m. Daniel Yekutieli, University of Tel Aviv, Israel

“New FDR Methodology for Complex Statistical Analysis of Genetic

Data”

5:00-5:15 p.m. Malgorzata Bogdan, Wroclaw University of Technology, Poland

“How to Modify Schwarz Bayesian Information Criterion to Locate

Multiple Interacting Quantitative Trait Loci”

6:30 – 7:30 p.m. Reception and Cash Bar North Ballroom, PMU

7:30 – 9:00 p.m. Workshop A Banquet North Ballroom, PMU

FRIDAY, JUNE 20

Registration, Stewart Center – East Foyer, 7:30 a.m. – 5:00 p.m.

8:00 – 8:30 a.m. Coffee and Donuts

8:30 – 10:00 a.m. Workshop A Session 3, STEW – Room 202

Chair: Jun Xie, Purdue University

8:30-9:00 a.m. William Muir, Purdue University

“Methods to Select for, or Map QTLs for Competitive Effects in Plants or

Animals''

9:00-9:30 a.m. Jayson Wilbur, Worcester Polytechnic Institute

“A Parametric Empirical Bayes Model for Multivariate Binary Data with Application to Microbial Community Characterization’’

9:30-9:45 a.m. Erik van Zwet, University of California, Berkeley

“Finding Transcription Factor Interactions”

10:00 – 10:30 a.m. Coffee Break

10:30 – 12:00 p.m. Workshop A Session 4, STEW – Room 202

Chair: Katy Simonsen, Purdue University

10:30-11:00 a.m. Lauren McIntyre, Purdue University

“Combining Mapping and Arraying: An Approach to Candidate Gene Identification”

11:00-11:30 a.m. Steve Smith, Nimblegen

“Microarrays from Micromirrors - and The Art of Array Redesign”

11:30-11:45 a.m. James Lyons-Weiler, University of Pittsburgh

“In Search of the PERfect Method: Best and Poorest Methods to Date for Normalization, Standardization, Finding Differentially Expressed Genes and Classification using Microarray Data”

12:00 p.m. – 1:30 p.m. Lunch (on your own)

1:30 – 3:30 p.m. Workshop A Session 5, STEW – Room 202

Chair: R.W. Doerge, Purdue University

1:30-2:00 p.m. David Siegmund, Stanford University

“Gene Mapping and Model Selection”

2:00-2:30 p.m. Priscilla E. Greenwood, Arizona State University

“QTL Inference From Perfect Marker Data”

2:30-3:00 p.m. Dachuang Cao, Purdue University

“A Maximum Likelihood Based Interval Mapping Method for Autopolyploids”

3:00-3:30 p.m. Zhiyi Chi, University of Chicago

“Filtering for Point Processes and Its Applications”

4:00 – 5:30 p.m. Myra Samuels Lecture MATH 175

Rob Tibshirani, Stanford University

“Least Angle Regression, Forward Stagewise and the Lasso”

6:00 – 8:00 p.m. Reception, Cash Bar and Poster Session West Main Lounge, PMU

SATURDAY, JUNE 21

Registration, Stewart Center – outside Room 202, 7:30 a.m. – 5:00 p.m.

8:00 – 8:30 a.m. Coffee and Donuts

8:30 – 10:00 a.m. Special Lectures I, STEW – Room 202

Chair: Mary Ellen Bock, Purdue University

1. Peter Hall, Australian National University, Australia

“Nonparametric Methods for Deconvolving Multiperiodic Functions”

2. Mathias Drton and Michael Perlman*, University of Washington

“A SINful Approach to Gaussian Graphical Model Selection”

3. Gordon Simons*, University of North Carolina-Chapel Hill and Sandor

Csorgo, University of Szeged, Hungary

“Pooling Strategies for St. Petersburg Gamblers”

8:30 – 10:00 a.m. Machine Learning I, STEW – Room 214AB

Chair: Michael Zhu, Purdue University

1. Xiaotong Shen, Ohio State University

“From Margin-Based Classification to psi-Learning”

2. Yi Lin, University of Wisconsin-Madison

“Support Vector Machine and Related Methods for Classification”

3. Eitan Greenshtein, Haifa University, Israel

“Low and High Dimensional Predictor Selection”

10:00 – 10:30 a.m. Coffee Break

10:30 – 12:30 p.m. Special Lectures II, STEW – Room 202

Chair: Jayanta Ghosh, Purdue University

1. Morris Eaton, University of Minnesota

“On Haar Predictive Inference and its Properties”

2. Peter McCullagh, University of Chicago

“An Exchangeable Clustering Model”

3. Willem van Zwet, University of Leiden, The Netherlands

“Collecting a Batch of Items on a Warehouse Carousel”

10:30 – 12:30 p.m. Session in Honor of Shanti S. Gupta: Order Statistics and Extreme Values, STEW – Room 214AB

Chair: N. Balakrishnan, McMaster University, Canada

1. H. N. Nagaraja, Ohio State University

“Characterizations Using Record Moments in a Random Record Model and Applications”

2. Glenn Hofmann, HSBC North America

“Can Progressive Censoring be “Better” Than Right Censoring?”

3. N. Kannan* and N. Balakrishnan, D. Kundu and U. K. T. Ng, University of Texas at San Antonio; McMaster University, Canada; Indian Institute of Technology, India; Southern Methodist University

“Step-Stress Models: Inference for the Exponential Distribution Under Type-II Censoring”

4. Chris Jones, The Open University, United Kingdom

“From Order Statistics Back to Ordinary Statistics”

12:30 p.m. – 1:30 p.m. Lunch (on your own)

1:30 – 3:00 p.m. Special Lectures III, STEW – Room 202

Chair: Willem van Zwet, University of Leiden, The Netherlands

1. Peter Bickel* and Ya’acov Ritov, University of California, Berkeley

“Boosting in General: Consistency and Minimaxity”

2. Larry Brown, University of Pennsylvania

TBA

1:30 – 3:00 p.m. New Advances in Nonparametric Function Approximation I, STEW –

Room 214AB

Chair, Jun Xie, Purdue University

1. Raymond Carroll, Texas A&M University

“Longitudinal and Clustered Data and Non/Semiparametric Regression”

2. Jianqing Fan, Chinese University of Hong Kong

“An Overview of Nonparametric Methods in Financial Economics”

3. Xihong Lin, University of Michigan

“Semiparametric Regression for Clustered/Longitudinal Data Using Profile-Kernel and Spline Methods”

1:30 – 3:00 p.m. Contributed Session I, STEW – Room 214CD

Chair: N. Kannan, University of Texas at San Antonio

1. Leming Qu, Boise State University

“Bayesian Wavelet Estimation of Partially Linear Models”

2 Laurence Freedman, Bar Ilan University and Gertner Institute for Epidemiology and Health Policy Research, Israel, and Ilya Novikov*, Gertner Institute for Epidemiology and Health Policy Research, Israel

“Decision Theoretic Set Estimates Based on the Point Loss Functions”

3. Harrison Zhou, Cornell University

“Infinitely Divisible Approximations for Nonparametric I.I.D. Experiments”

3:00 – 3:30 p.m. Coffee Break

3:30 – 5:30 p.m. New Advances in Nonparametric Function Approximation II, STEW –

Room 202

Chair: Larry Brown, University of Pennsylvania

1. Tony Cai, University of Pennsylvania

“On Block Thresholding For Wavelet Function Estimation”

2. Sam Efromovich, University of New Mexico

“Nonparametric Estimation: From Asymptotic to Small Sample Sizes”

3. Mark Low, University of Pennsylvania

“Adaptive Estimation of Linear Functionals”

4. Cun-Hui Zhang, Rutgers University

“Minimax Compound Estimation”

3:30 – 5:00 p.m. Session in Honor of Shanti S. Gupta: Ranking and Selection, STEW – Room 214AB

Chair: H. N. Nagaraja, Ohio State University

1 TaChen Liang, Wayne State University

“Simultaneous Variable Sampling Inspection for Finite Population”

2 Klaus Miescke* and Ken Ryan, University of Illinois at Chicago

“On Gupta’s Subset Selection Rule under Normality”

3. Pinyuen Chen*, Syracuse University and S. Panchapakesan, Southern

Illinois University

“Applications of Ranking and Selection Theory in Signal Processing”

3:30 – 5:30 p.m. Bayesian Methods for High Dimensional Computing, STEW – Room 214CD

Chair: Siddhartha Chib, Washington University

1. Ming-Hui Chen, University of Connecticut

“On Propriety of the Posterior Distribution and Existence of the Maximum Likelihood Estimator for Regression models with Missing Covariates”

2. Dipak Dey, University of Connecticut

“Bayesian Criterion Based Model Assessment for Categorical Data”

3. Bani Mallick*, Texas A&M University, Debashis Ghosh, University of

Michigan and Malay Ghosh, University of Florida

“Bayesian Classification of Tumors Using Gene Expression Data”

4. Debajyoti Sinha, Medical University of South Carolina and Tapabrata Maiti, Iowa State University

“Models and Bayesian Analysis of Recurrent Events Data with Dependent Termination”

6:00 p.m. - Taste of Tippecanoe Downtown, Lafayette

SUNDAY, JUNE 22

Registration, Stewart Center – outside Room 202, 7:30 a.m. – 5:00 p.m.

8:00 – 8:30 a.m. Coffee and Donuts

8:30 – 10:00 a.m. Validation of Complex Computer Models, STEW – Room 202

Chair: Gary McDonald, Oakland University and National Institute of

Statistical Sciences

1. Jerry Sacks, Duke University

“Statistical Validation of Computer Models I”

2. Jim Berger, Duke University

“Statistical Validation of Computer Models II”

8:30 – 10:00 a.m. Machine Learning II, STEW – Room 214AB

Chair: Jayson Wilbur, Worcester Polytechnic Institute

1. J. S. Marron, University of North Carolina

“Distance Weighted Discrimination and Geometrical Representation

of High Dimension - Low Sample Size Data”

2. H. A. Chipman, E. I. George and R. E. McCulloch*, University of Waterloo, Canada; University of Pennsylvania; University of Chicago

“BART: Bayesian Additive Regression Trees”

3. Peter Bickel, University of California, Berkeley and Elizaveta Levina*, University of Michigan

“The Benefits of Assuming Independence in Classification When

There Are Many More Variables Than Observations”

10:00 – 10:30 p.m. Coffee Break

10:30 – 12:00 p.m. Special Lectures IV, STEW – Room 202

Chair: Morris Eaton, University of Minnesota

1. Gary McDonald, Oakland University and National Institute of Statistical

Sciences

“A Characterization of the Ridge Regression Trace”

2. Anna Amirdjanova and Michael Woodroofe*, University of Michigan

“Shrinkage Estimation for Shape Restricted Regression”

10:30 – 12:00 p.m. Bayesian Analysis I: Nonparametrics and Semiparametrics, STEW - - Room 214AB

Chair: Dongchu Sun, University of Missouri-Columbia

1. Samiran Sinha, Bhramar Mukherjee, Malay Ghosh*, University of Florida and Bani K. Mallik, Raymond J. Carroll, Texas A&M University

“Semiparametric Bayesian Analysis of Matched Case-Control Studies”

2. Jaeyong Lee, Pennsylvania State University

“Nonparametric Bayesian Survival Analysis”

3. Jayaram Sethuraman, Florida State University

“Bayesian Estimation in Repair Models”

10:30 – 12:00 p.m. Machine Learning III, STEW – Room 214CD

Chair: Elizaveta Levina, University of Michigan

1. Tsachy Weissman, Stanford University and HP Labs

“Context-Based Discrete Denoising: A Universally Optimal and Practical Scheme”

2. Michael Jordan, University of California, Berkeley

“Convex Analysis, Convex Optimization and Statistical Inference”

12:00 – 1:30 p.m. Lunch (on your own)

1:30 – 3:00 p.m. Bayesian Analysis II: Model Checking, Robustness and Estimation, STEW – Room 202

Chair: Malay Ghosh, University of Florida

1. M. J. Bayarri*, University of Valencia and M. E. Castellanos, Migual Hernandez University, Spain

“Bayesian Checking of Hierarchical Models”

2. Herman Rubin, Purdue University

“Prior Bayes Robustness: It Can Be Done”

3. Dongchu Sun* and Xiaoqian Sun, University of Missouri-Columbia

“Estimation of the Precision and Covariance Matrices in the Generalized Butterfly Model”

1:30 - 3:00 p.m. All About Data Depth, STEW – Room 214AB

Chair: Regina Liu, Rutgers University

1. Peter J. Rousseeuv, Renaissance Technologies Corporation

“The Deepest Regression Method”

2. Yijun Zuo, Michigan State University

“Multivariate Medians and Weighted Means Based on Data Depth”

3. Kesar Singh, Rutgers University

“Multivariate Methods Derived from Data Depth”

1:30 – 3:00 p.m. Contributed II, STEW – Room 214CD

Chair: Colin Chen, SAS Institute Inc.

1. Debasis Bhattacharya, Visva-Bharati University, India

“On the Comparative Performance of Bayesian and Classical Point Estimators Under Asymmetric Loss”

2. Ben Hansen, University of Michigan

“Minimax Expected Length Binomial Confidence Procedure”

3. Anatoly Naumov, Novosibirsk State Technical University, Russia

“A New Approach to Sequential Control of Experiments Problems”

3:00 – 3:30 p.m. Coffee Break

3:30 – 5:00 p.m. Asymptotics, STEW – Room 202

Chair: Peter Bickel, University of California, Berkeley

1. Priscilla E. Greenwood, Arizona State University

“Asymptotic Efficiency of Semi-Parametric Semi-Markov Process Estimators”

2. Ya’acov Ritov, The Hebrew University, Israel

“Hidden Markov Model, Maximum Likelihood and Derivative”

3. Sara van der Geer, University of Leiden, the Netherlands

“Penalized Empirical Risk Minimization in Classification”

3:30 – 5:00 p.m. Bioequivalence, STEW – Room 214AB

Chair: Ravi Khattree, Oakland University

1. Hari Iyer, Colorado State University

“Bioequivalence Criteria and Related Inference Procedures”

2. Pulak Ghosh, Oakland University

“A Bayesian Approach to Bioequivalence Trials”

3:30 – 5:00 p.m. Contributed III, STEW – Room 214CD

Chair: Tonglin Zhang, Purdue University

1. Colin Chen*, SAS Institute Inc. and Shanti S. Gupta, Purdue University

“Selection from Double Exponential Distribution Using Empirical Bayes

Approach”

2. B. O. Omolo, Texas Tech University

“Aligned Rank Statistics for Repeated Measurement Models with

Orthonormal Design Employing a Chernoff-Savage Approach”

3. Friedrich Liese, University of Rostock, Germany

“Selection Procedures for Sparse Data”

6:00 – 7:00 p.m. Reception and Cash Bar East and West Faculty Lounge, PMU

7:00 – 9:00 p.m. Conference and Workshop B Banquet East and West Faculty Lounge, PMU

MONDAY, JUNE 23

Registration, Stewart Center – Room 110, 7:30 a.m. – 5:00 p.m.

I. PROGRAM FOR WORKSHOP B

8:00 – 8:30 a.m. Coffee and Donuts

8:30 – 10:00 a.m. Multiple Comparison and Mixture Models, STEW – Room 202

Chair: Jayanta Ghosh, Purdue University

1. Rich Charnigo and Jiayang Sun*, Case Western Reserve University

“Testing Homogeneity in a Mixture Distributions”

2. Jiashun Jin, Stanford University

“Detecting and Estimating Sparse Mixtures”

3. Timothy Costigan, Eli Lilly and Company

“Factor Analytic Covariance Structure and Multiple Testing”

10:00 – 10:30 a.m. Coffee Break

10:30 – 12:30 p.m. Special Lectures, STEW – Room 202

Chair: Sanat Sarkar, Temple University

1. Yoav Benjamini, Tel Aviv University, Israel

“What Can Be Learned about False Discovery Rates from a Very Large Problem?”

2. Samuel Kou, Harvard University

“Bayesian Analysis of Single Molecule Experiments”

3. Xiangqin Cui, J.T.Gene Hwang*, Natalie Blades, Jing Qiu and Gary Churchill, Jackson Laboratory and Cornell University

“Should We Assume Identical or Entirely Different Population Variances in Testing a Large Number of Population Means such as in Microarray Analysis? Let Data Decide and Do Better”

12:30 – 1:30 p.m. Lunch (on your own)

1:30 – 3:00 p.m. False Discovery Rates, STEW – Room 202

Chair: Yoav Benjamini, Tel Aviv University, Israel

1. Jiayang Sun and Zhongfa Zhang*, Case Western Reserve University

“New Procedures for Controlling False Discovery Rate”

2. Sanat Sarkar, Temple University

“False Discovery Rates in Single-Step Multiple Testing Procedures”

3. Helmut Finner, University of Dusseldorf, Germany

“On the False Discovery Rate”

3:00 – 3:30 p.m. Coffee Break

3:30 – 5:00 p.m. Mixture Models, STEW – Room 202

Chair: Dipak Dey, University of Connecticut

Sanjib Basu, North Illinois University

“A Bayesian Approach to Multiple Testing”

Siddhartha Chib, Washington University

“Modeling and Analysis of Treatment-Response Data”

Sujit Sahu, University of Southampton

“A Fast Distance Based Approach for Determining the Number of Components in Mixtures”

II. PROGRAM FOR WORKSHOP C

8:00 – 8:30 a.m. Coffee and Donuts

8:30 – 10:00 a.m. Structure and Funding of Consulting Services, STEW – Room

214ABCD

10:00 – 10:30 a.m. Coffee Break

10:30 – 12:00 p.m. Accountability and Reports, STEW – Room 214ABCD

12:00 – 1:30 p.m. Lunch (on your own)

1:30 – 3:00 p.m. Preparation of Graduate Student Consultants, STEW – Room

214ABCD

3:00 – 3:30 p.m. Coffee Break

3:30 – 5:00 p.m. Grant Proposal Writing and Short Courses, STEW – Room 214ABCD

5:00 – 7:00 p.m. Reception, Cash Bar and Poster Session East and West Faculty Lounge, PMU

7:00 – 9:00 p.m. Workshop C Banquet East and West Faculty Lounge, PMU

TUESDAY, JUNE 24

PROGRAM FOR WORKSHOP C

8:00 – 8:30 a.m. Coffee and Donuts

8:30 – 10:00 a.m. Institutional Review Boards, STEW – Room 202, 214CD

10:00 – 10:30 a.m. Coffee Break

10:30 – 12:00 p.m. Ethics, STEW – Room 202, 214CD