JSM 2017 Online Program

Legend:
CC = Baltimore Convention Center, H = Hilton Baltimore
* = applied session ! = JSM meeting theme

Activity Details

214696	Sun, 7/30/2017, 1:30 PM - 4:30 PM	H-Poe A
IMS Executive Committee Meeting — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director

5 !	Sun, 7/30/2017, 2:00 PM - 3:50 PM	CC-314
New Developments in Functional Data — Invited Papers
IMS , Section on Nonparametric Statistics
Organizer(s): Aurore Delaigle, University of Melbourne
Chair(s): Marianna Pensky, University of Central Florida
2:05 PM	From Brain to Hand to Statistics with Dynamic Smoothing — James O. Ramsay, McGill University
2:30 PM	Testing Curvature in Functional Single Index Models: Inference for Reaction Norms in Ecology — Giles J Hooker, Cornell University ; Zi Ye, Cornell University
2:55 PM	Mixture Inner Product Spaces and Their Application to Functional Data Analysis — Hans-Georg G Müller, University of California, Davis ; Fang Yao, University of Toronto ; Zhenhua Lin, University of Toronto
3:20 PM	Clusering functional data using projections — Aurore Delaigle, University of Melbourne ; Peter Hall, University of Melbourne ; Tung Pham, University of Melbourne
3:45 PM	Floor Discussion

12 * !	Sun, 7/30/2017, 2:00 PM - 3:50 PM	CC-Ballroom I
Bridging BFF (Bayesian/Fiducial/Frequentist) Inference in the Era of Data Science — Invited Papers
IMS , Section on Bayesian Statistical Science , Section on Statistical Consulting
Organizer(s): Dongchu Sun, University of Missouri
Chair(s): Dongchu Sun, University of Missouri
2:05 PM	BFF Inferences with Rs: Replications, Relevance and Robustness — Xiao-Li Meng, Harvard University ; Keli Liu, Stanford University
2:30 PM	The Use of Rejection Odds and Rejection Ratios in Testing Hypotheses — James Berger, Duke University ; Daniel Benjamin, University of Southern California ; Thomas Sellke, Purdue University
2:55 PM	New Perspectives of P-Value and C-Factor for Hypothesis Testing — Regina Y Liu, RUTGERS UNIVERSITY ; Sifan Y Liu, RUTGERS UNIVERSITY ; MINGE Y XIE, RUTGERS UNIVERSITY
3:20 PM	Floor Discussion

15 * !	Sun, 7/30/2017, 2:00 PM - 3:50 PM	CC-343
Networks, Multivariate Analysis, and Time Series — Topic Contributed Papers
Royal Statistical Society , IMS , IEEE Computer Society
Organizer(s): Jan Beran, University of Konstanz
Chair(s): Jan Beran, University of Konstanz
2:05 PM	Network Time Series Modeling — Marina Knight, University of York ; Matthew Nunes, Lancaster University ; Guy Nason, University of Bristol
2:25 PM	On Aggregation of Strongly Dependent Network Flows — Jan Beran, University of Konstanz ; Sucharita Ghosh, Swiss Federal Research Institute WSL ; Haiyan Liu, University of Leeds
2:45 PM	A Wavelet Lifting Approach to Long Memory Estimation — Matthew Nunes, Lancaster University ; Marina Knight, University of York ; Guy Nason, University of Bristol
3:05 PM	A Framework for the Online Monitoring and Analysis of Multi-Gigabit Network Streams — Stilian Stoev, University of Michigan ; Michalis Kallitsis, Merit Network ; George Michailidis, University of Florida ; Shrijita Bhattacharya, University of Michigan ; Zheng Gao, University of Michigan
3:25 PM	Semiparametric, Parametric and Possibly Sparse Models for Multivariate Long-Range Dependence — Vladas Pipiras, University Od North Carolina At Chaple Hill ; Stefanos Kechagias, SAS Institute ; Changryong Baek, Sungkyunkwan University
3:45 PM	Floor Discussion

16 !	Sun, 7/30/2017, 2:00 PM - 3:50 PM	CC-340
Recent Advances and Challenges in High-Dimensional Data Analysis — Topic Contributed Papers
Section on Statistical Learning and Data Science , IMS , Section on Nonparametric Statistics
Organizer(s): Pierre Bellec, Rutgers University
Chair(s): Dan Yang, Rutgers University
2:05 PM	On the Asymptotic Performance of Bridge Estimators — Arian Maleki, Columbia Univ ; Haolei Weng, Columbia University ; Shuaiwen Wang, Columbia University
2:25 PM	A General Framework for Uncovering Dependence Networks — Johannes Lederer, University of Washington
2:45 PM	The Generalized Lasso Problem and Uniqueness — Alnur Ali ; Ryan Tibshirani, Carnegie Mellon University
3:05 PM	Distributed Statistical Estimation and Rates of Convergence in Normal Approximation — Stanislav Minsker, University of Southern California
3:25 PM	Slope Meets Lasso in Sparse Linear Regression — Pierre Bellec, Rutgers University
3:45 PM	Floor Discussion

43	Sun, 7/30/2017, 4:00 PM - 5:50 PM	CC-329
Statistical Methods for Complex Networks — Invited Papers
IMS , International Indian Statistical Association , National Science Foundation
Organizer(s): Po-Ling Loh, UW-Madison
Chair(s): Po-Ling Loh, UW-Madison
4:05 PM	Analysis of Centrality in Sublinear Preferential Attachment Trees — Varun Suhas Jog, University of Wisconsin - Madison ; Po-Ling Loh, UW-Madison
4:35 PM	Community Detection and Invariance to Distribution — Guy Bresler, MIT ; Wasim Huleihel, MIT
4:55 PM	DNA Seriation Under Planted Hamiltonian Path Model — Jiaming Xu, Purdue University
5:20 PM	Statistical Inference Problems in Growing Random Graphs — Miklos Z Racz, Microsoft Research
5:45 PM	Floor Discussion

49 * !	Sun, 7/30/2017, 4:00 PM - 5:50 PM	CC-331/332
Statistical Inference for Large-Scale Financial Data — Invited Papers
IMS , Business and Economic Statistics Section , Society for Risk Analysis , Statistics in Business Schools Interest Group
Organizer(s): Yingying Li, Hong Kong University of Science and Technology
Chair(s): Yingying Li, Hong Kong University of Science and Technology
4:05 PM	Robust High-Dimensional Volatility Matrix Estimation for High-Frequency Factor Model — Jianqing Fan, Princeton University ; Donggyu Kim, Princeton University
4:30 PM	Solve Financial Problems by Quantum Computing — Yazhen Wang, University of Wisconsin Madison
4:55 PM	Inference on Risk Premia Without a Fully Specified Factor Model — Dacheng Xiu, University of Chicago ; Stefano Giglio, University of Chicago
5:20 PM	Testing and Scoring High-dimensional Covariance Matrices When Heteroscedasticity is Present — Xinghua Zheng, HKUST ; Xinxin Yang, HKUST ; Jiaqi Chen, Harbin Institute of Technology ; Hua Li, Chang Chun University
5:45 PM	Floor Discussion

51 !	Sun, 7/30/2017, 4:00 PM - 5:50 PM	CC-326
Large-Scale Global and Simultaneous Inference — Invited Papers
IMS
Organizer(s): Wenguang Sun, University of Southern California
Chair(s): Wenguang Sun, University of Southern California
4:05 PM	Hypothesis Testing of Matrix Graph Model — Yin Xia, Fudan University
4:30 PM	Inference Following Aggregate Level Hypothesis Testing in Large Scale Genomic Data — Ruth Heller, Tel-Aviv University ; Nilanjan Chatterjee, Johns Hopkins University ; Abba Krieger, University of Pennsylvania ; Jianxin Shi, National Cancer Institute
4:55 PM	New Approaches to Multiple Testing of Grouped Hypotheses — Sanat K. Sarkar, Temple University
5:20 PM	Confidence regions for spatial excursion sets from repeated random field observations, with an application to climate — Max Sommerfeld, Universität Göttingen ; Stephen Sain, The Climate Corporation ; Armin Schwartzman, University of California, San Diego
5:45 PM	Floor Discussion

61	Sun, 7/30/2017, 4:00 PM - 5:50 PM	CC-325
New Developments in Complex Time Series Data — Topic Contributed Papers
IMS , Business and Economic Statistics Section , International Chinese Statistical Association
Organizer(s): Han Xiao, Rutgers University
Chair(s): Dong Wang, Princeton University
4:05 PM	A NEW APPROACH to DIMENSION REDUCTION for MULTIVARIATE TIME SERIES — Xiaofeng Shao, University of Illinois, At Urbana-Champaign
4:25 PM	Constrained Factor Model for High-Dimensional Matrix-Variate Time Series — Yi Chen, Rutgers Univ Statistics Dept ; Rong Chen, Rutgers University
4:45 PM	GRADIENT-BASED STRUCTURAL CHANGE DETECTION for NON-STATIONARY TIME SERIES M-ESTIMATION — Zhou Zhou, University of Toronto
5:05 PM	White Noise Test for High-Dimensional Time Series — Han Xiao, Rutgers University
5:25 PM	Baxter's Inequality and Sieve Bootstrap for Random Fields — Jens-Peter Kreiss, TU Braunschweig ; Marco Meyer, TU Braunschweig ; Carsten Jentsch, University of Mannheim
5:45 PM	Floor Discussion

83	Sun, 7/30/2017, 8:30 PM - 10:30 PM	CC-Halls A&B
Your Invited Poster Evening Entertainment: No Longer Board — Invited Poster Presentations
Astrostatistics Special Interest Group , Biometrics Section , Biopharmaceutical Section , Business and Economic Statistics Section , ENAR , Government Statistics Section , IMS , International Society for Bayesian Analysis (ISBA) , Section for Statistical Programmers and Analysts , Section on Statistical Consulting , Section on Statistical Education , Section on Statistical Learning and Data Science , Section on Statistics and the Environment , Social Statistics Section , Survey Research Methods Section , Section on Statistics in Genomics and Genetics
Chair(s): Jessi Cisewski, Yale University
1:	Overview of SAMSI Program on Statistical, Mathematical and Computational Methods for Astronomy (ASTRO) — Gutti Jogesh Babu, The Pennsylvania State University ; David Jones, SAMSI / Duke
2:	A Multi-Resolution 3D Map of the Intergalactic Medium via the Lyman-Alpha Forest — Collin Eubanks, Carnegie Mellon University ; Jessi Cisewski, Yale University ; Rupert Croft, Carnegie Mellon University ; Doug Nychka, National Center for Atmospheric Research ; Larry Wasserman, Carnegie Mellon
3:	Testing Bayesian Galactic Mass Estimates Using Outputs from Hydrodynamical Simulations — Gwendolyn Eadie, McMaster University ; Benjamin Keller, McMaster University ; William Harris, McMaster University ; Aaron Springford, Queen's University
4:	Quantifying Discovery in Astro/Particle Physics: Frequentist and Bayesian Perspectives — David Van Dyk, Imperial College London ; Sara Algeri, Imperial College London ; Jan Conrad, University of Stockholm
5:	Computer Model Calibration to Enable Disaggregation of Large Parameter Spaces, with Application to Mars Rover Data — David Craig Stenning, SAMSI/Duke University ; Working Group 1 ASTRO Program, SAMSI
6:	The Association Between Copy Number Aberration, DNA Methylation, and Gene Expression — Wei Sun, Fred Hutchinson Cancer Research Center
7:	Rerandomization: a Flexible Framework for Experimental Design — Kari Lock Morgan, Penn State University
8:	IMs for IVs: An Inferential Model Approach to Instrumental Variable Regression — Nicholas Aaron Syring, NCSU ; Ryan Martin, NCSU
9:	Detecting Differential Gene Expression by Single-Cell RNA Sequencing — Mingyao R Li, University of Pennsylvania ; Cheng Jia, University of Pennsylvania ; Nancy Ruonan Zhang, Wharton School , University of Pennsylvania
10:	Statistical Science and Policy at the EPA — Elizabeth Mannshardt, US Environmental Protection Agency
11:	Approximate Message Passing Algorithms for High-Dimensional Regression — Cynthia Rush, Columbia University
12:	Generalized Fiducial Inference for High-Dimensional Data — Jan Hannig, University of North Carolina at Chapel Hill ; Jonathan P Williams, University of North Carolina at Chapel Hill
13:	The Combination of Confirmatory and Contradictory Statistical Evidence at Low Resolution — Ruobin Gong, Harvard University ; Xiao-Li Meng, Harvard University
14:	Approximate Confidence Distribution Computing: An Effective Likelihood-Free Method with Statistical Guarantees — Suzanne Thornton, Rutgers University ; Minge Xie, Rutgers University
15:	R Package TDA for Statistical Inference on Topological Data Analysis — Jisu Kim, Carnegie Mellon University
16:	Teaching a Large, Project-Based Statistical Consulting Class — Emily Griffith, NC State University
17:	Transforming Undergraduate Statistics Education Through Experiential Learning: It's Essential! — Tracy Morris, University of Central Oklahoma ; Cynthia Murray, University of Central Oklahoma ; Tyler Cook, University of Central Oklahoma
18:	The Geometry of Synchronization Problems and Learning Group Actions — Tingran Gao, Duke University ; Jacek Brodzki, University of Southampton ; Sayan Mukherjee, Duke University
19:	Sufficient Markov Decision Processes with Alternating Deep Neural Networks — Longshaokan Wang, North Carolina State University ; Eric Laber, North Carolina State University ; Katie Witkiewitz, University of New Mexico
20:	Optimal Dynamic Treatment Regimes Using Decision Lists — Yichi Zhang, Harvard University ; Eric Laber, North Carolina State University ; Anastasios (Butch) Tsiatis, North Carolina State University ; Marie Davidian, North Carolina State University
21:	Predicting Phenotypes from Microarrays Using Amplified, Initially Marginal, Eigenvector Regression — Lei Ding, Indiana University ; Daniel J. McDonald, Indiana University
22:	Computer Vision Meets Television — Taylor Arnold, University of Richmond ; Lauren Tilton, University of Richmond
23:	Generalized Fiducial Inference for Nonparametric Function Estimation — Randy C.S. Lai, University of Maine
24:	A Phylogenetic Transform Enhances Analysis of Compositional Microbiota Data — Justin David Silverman, Duke University ; Sayan Mukherjee, Duke University ; Lawrence A David, Duke University
25:	Bayesian Multispecies Ecological Models for Paleoclimate Reconstruction Using Inverse Prediction — John Tipton, Colorado State University ; Mevin Hooten, Colorado State University
26:	Fast Maximum Likelihood Inference for Spatial Generalized Linear Mixed Models — Yawen Guan, Penn State University ; Murali Haran, Pennsylvania State University
27:	Fair Prediction with Disparate Impact: a Study of Bias in Recidivism Prediction Instruments — Alexandra Chouldechova, Carnegie Mellon University
28:	I Ran a Nonresponse Follow-Up Survey; Now What Do I Do? — Phillip Kott, RTI

91 !	Mon, 7/31/2017, 8:30 AM - 10:20 AM	CC-340
Statistical Methods for Analysis of Time-Varying Network Data — Invited Papers
Section on Nonparametric Statistics , IMS , Section on Statistical Computing
Organizer(s): Marianna Pensky, University of Central Florida
Chair(s): Aurore Delaigle, University of Melbourne
8:35 AM	Summaries of Networks in Time — Sofia Olhede, UCL
9:00 AM	Oracle Inequalities for the Dynamic Stochastic Block Model and Time-Dependent Graphon — Marianna Pensky, University of Central Florida
9:25 AM	Nonparametrics, Network Information and Efficient Estimation — Patrick Wolfe, University College London
9:50 AM	The Block Point Process Model for Continuous-Time Event-Based Dynamic Networks — Kevin Shuai Xu, University of Toledo ; Ruthwik Junuthula, University of Toledo ; Haghdan Maysam, University of Toledo ; Devabhaktuni Vijay, University of Toledo
10:15 AM	Floor Discussion

92	Mon, 7/31/2017, 8:30 AM - 10:20 AM	CC-341
Computational Challenges in Statistics — Invited Papers
IMS , Section on Statistical Learning and Data Science
Organizer(s): Sahand Negahban, Yale University
Chair(s): Sahand Negahban, Yale University
8:35 AM	Pairwise Comparison Models for High-Dimensional Ranking: Some Statistical and Computational Trade-Offs — Sivaraman Balakrishnan, Department of Statistics, CMU ; Nihar B Shah, Univ of California - Berkeley ; Martin J. Wainwright, EECS and Statistics, University of California, Berkeley
9:00 AM	On the Kiefer-Wolfowitz MLE for Gaussian Mixtures — Adityanand Guntuboyina, UC Berkeley
9:25 AM	Modeling Disease Propagation in Networks: Source-Finding and Influence Maximization — Po-Ling Loh, UW-Madison
9:50 AM	Guaranteed Tensor PCA with Optimality in Statistics and Computation — Anru Zhang, University of Wisconsin-Madison ; Dong Xia, University of Wisconsin-Madison
10:15 AM	Floor Discussion

100	Mon, 7/31/2017, 8:30 AM - 10:20 AM	CC-308
Medallion Lecture I — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
Chair(s): Alan Karr, RTI International
8:35 AM	Design and Analysis of Randomized Experiments on Networks — Edoardo M. Airoldi, Harvard University
10:15 AM	Floor Discussion

101	Mon, 7/31/2017, 8:30 AM - 10:20 AM	CC-310
Foundation for Big Data Analysis — Invited Papers
IMS , Section on Statistical Learning and Data Science , Section on Nonparametric Statistics , Section for Statistical Programmers and Analysts
Organizer(s): Jianqing Fan, Princeton University
Chair(s): Jianqing Fan, Princeton University
8:35 AM	Inference for Large Networks — Peter Bickel, UC Berkeley ; purna sarkar, u. of texas ; Soumendu Mukherjee, UC Berkeley
9:00 AM	Inference for Big Data — Larry Wasserman, Carnegie Mellon
9:25 AM	Eigenvalues and Variance Components — Iain M Johnstone, Stanford Universty
9:50 AM	Error Variance Estimation in Ultra-High Dimensional Regression Models — Runze Li, The Pennsylvania State University ; Zhao Chen, The Pennsylvania State University ; Jianqing Fan, Princeton University
10:15 AM	Floor Discussion

106 * !	Mon, 7/31/2017, 8:30 AM - 10:20 AM	CC-346
Empirical Transforms, Saddlepoint Approximations, and Risk Assessment with Some Applications — Topic Contributed Papers
Section on Risk Analysis , Business and Economic Statistics Section , IMS
Organizer(s): Sucharita Ghosh, Swiss Federal Research Institute WSL
Chair(s): Sucharita Ghosh, Swiss Federal Research Institute WSL
8:35 AM	Estimation of the Tail Index Using Semiparametric Regression — Emanuele Taufer, University of Trento ; Mofei Jia, Xi'an Jiaotong-Liverpool University ; Maria Michela Dickson, University of Trento
8:55 AM	On Distributions of Ratios — Simon Broda, University of Amsterdam ; Raymond Kan, University of Toronto
9:15 AM	An Empirical Saddlepoint Approximation Based Method for Smoothing Survival Functions Under Right Censoring — Adao Trindade, Texas Tech University ; Pratheepa Jeganathan , Stanford University ; Noroharivelo Randrianampy, HECMMA ; Robert Paige, Missouri University of Science and Technology
9:35 AM	Portfolio Selection with Active Risk Monitoring — Pawel Polak, Columbia University ; Marc Paolella, University of Zurich
9:55 AM	Discussant: Keith Knight, Professor, Department of Statistical Sciences, University of Toronto
10:15 AM	Floor Discussion

139 !	Mon, 7/31/2017, 10:30 AM - 12:20 PM	CC-320
Challenges and Advances in Statistical Inference for Problems with Nonregularity in the Era of Big Data — Invited Papers
WNAR , Biometrics Section , IMS
Organizer(s): Youyi Fong, Fred Hutchinson Cancer Research Center
Chair(s): Kenneth Rice, University of Washington
10:35 AM	Model-Robust Inference for Continuous Threshold Regression Models — Chongzhi Di, Fred Hutchinson Cancer Research Center ; Ying Huang, Fred Hutchinson Cancer Research Center ; Peter Gilbert, Fred Hutchinson Cancer Research Center ; Youyi Fong, Fred Hutchinson Cancer Research Center
10:55 AM	Local M-Estimation with Discontinuous Criterion for Dependent and Limited Observations — Myung Hwan Seo, SEOUL NATIONAL UNIVERSITY ; Taisuke Otsu, London School of Economics
11:15 AM	Intelligent Sampling for Identifying Thresholds in Observed Databases and Time Series — Zhiyuan Lu, University of Michigan ; Moulinath Banerjee, University of Michigan ; George Michailidis, University of Florida
11:35 AM	Marginal Screening in Case-Control Studies — Min Qian, Columbia University ; Ian McKeague, Columbia University
11:55 AM	Clustering Functional Databased on Change-Point Models for Electronic Monitoring Data — Chongzhi Di, Fred Hutchinson Cancer Research Center ; Yifan Zhu, Fred Hutchinson Cancer Research Center ; Ying Qing Chen, Fred Hutchinson Cancer Research Center
12:15 PM	Floor Discussion

144 !	Mon, 7/31/2017, 10:30 AM - 12:20 PM	CC-336
Uncover the Essential Truth by Integrating Big and Complex Imaging Data with New Statistical Tools — Invited Papers
SSC , IMS , Section on Statistics in Imaging , Section for Statistical Programmers and Analysts
Organizer(s): Linglong Kong, University of Alberta
Chair(s): Adam Kashlak, Univ of Cambridge
10:35 AM	A Bayesian Approach to SENSE Image Reconstruction in fMRI — Daniel B. Rowe, Marquette University
11:00 AM	A Hierarchy of Brain Networks Revealed by MVPA Performance Metrics — Stephen Strother, Baycrest & University of Toronto ; Cheryl Grady, Baycrest & University of Toronto
11:25 AM	Classification Using the Morlet Transform for fMRI Data — Debashis Ghosh, Colorado School of Public Health ; Manish Dalwani, Colorado School of Medicine
11:50 AM	A Potts Mixture Spatiotemporal Joint Model for Combined MEG and EEG Data — Yin Song, University of Victoria ; Farouk Nathoo, University of Victoria
12:15 PM	Floor Discussion

145 * !	Mon, 7/31/2017, 10:30 AM - 12:20 PM	CC-315
Statistical Methods in Data Integration and Data Harmonization — Invited Papers
ENAR , WNAR , IMS , Section on Statistics in Imaging , Section on Statistics in Genomics and Genetics
Organizer(s): Peter XK Song, University of Michigan,
Chair(s): Peter XK Song, University of Michigan,
10:35 AM	Generalized Meta-Analysis: Towards an Unified Paradigm for Model Building Through Integration of Disparate Data Sources — Nilanjan Chatterjee, Johns Hopkins University ; Runlong Tang, Johns Hopkins University ; Prosenjit Kundu, Johns Hopkins University
11:00 AM	Meta-Analysis with Extremely Small Number of Studies — Lu Tian, Stanford University ; Minge Xie, Rutgers University ; LJ Wei, Harvard University
11:25 AM	Integrating Imaging and Genetic Data for Understanding Neuropsychological Disorders — Heping Zhang, Yale University School of Public Health ; Canhong Wen, Sun Yat-Sen University ; Chintan Mehta, Yale University
11:50 AM	Discussant: Ryan Martin, NCSU
12:15 PM	Floor Discussion

146	Mon, 7/31/2017, 10:30 AM - 12:20 PM	CC-310
Blackwell Lecture — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
Chair(s): Sahand Negahban, Yale University
10:35 AM	Information-Theoretic Methods in Statistics: From Privacy to Optimization — Martin J. Wainwright, EECS and Statistics, University of California, Berkeley
12:15 PM	Floor Discussion

147 * !	Mon, 7/31/2017, 10:30 AM - 12:20 PM	CC-328
Bayesian Hierarchical Modeling: Obtaining Optimal Performance Through Theoretical Understanding — Invited Papers
IMS , Section on Bayesian Statistical Science
Organizer(s): James Berger, Duke University
Chair(s): James Berger, Duke University
10:35 AM	Posterior Concentration for Bayesian Regression Trees and their Ensembles — Veronika Rockova, University of Chicago ; Stephanie van der Pas, Leiden University
11:00 AM	Large-P Small-N Nonparametric Regression and Additive-Interactive Response Functions — Surya T Tokdar, Duke University
11:25 AM	An Objective Prior for Hyperparameters in Normal Hierarchical Models — Dongchu Sun, University of Missouri
11:50 AM	Discussant: Edward I. George, Wharton, University of Pennsylvania
12:15 PM	Floor Discussion

161	Mon, 7/31/2017, 10:30 AM - 12:20 PM	CC-325
SPEED: Nonparametrics and Imaging — Contributed Speed
Section on Nonparametric Statistics , Section on Statistics in Imaging , SSC , IMS
Chair(s): Suzanne Thornton, Rutgers University
10:40 AM	Automatic Shape-Constrained Nonparametric Regression — Zhikun Gao, George Washington University ; Huixia Judy Wang, The George Washington University ; Yanlin Tang, School of Mathematical Sciences, Tongji University
10:45 AM	Nonparametric Modeling of Heavy-Tailed Distributions with Applications to Extreme Events — Todd Wilson, North Carolina State University ; Sujit K Ghosh, North Carolina State University
10:50 AM	Instrument Assisted Partial-Linear Single Index Regression for Errors in Variables Models with Binary Response — Qianqian Wang, University of South Carolina ; Yanyuan Ma, Penn State University ; Guangren Yang, Jinan University ; Xia Cui, Zhongshan University
11:00 AM	Estimation of Locally Stationary Spatial Processes with Applications to the American Community Survey — Daniel Weinberg, U.S. Census Bureau ; Tucker McElroy, U. S. Census Bureau ; Soumendra N Lahiri, North Carolina State University
11:05 AM	A Comparison of Testing Methods in Scalar-On-Function Regression — Merve Tekbudak, North Carolina State University ; Marcela Alfaro Córdoba, North Carolina State University ; Ana-Maria Staicu, North Carolina State University, Department of Statistics ; Arnab Maity, North Carolina State University
11:10 AM	Weighted Quantile Regression Splines using Total Variation Regularization — Jae-Hwan Jhong, Korea University ; Ja-Yong Koo, Korea University
11:20 AM	Bayesian Methods for Image Texture Analysis with Applications to Cancer Radiomics — Xiao Li, University of Texas, School of Public Health, Department of Biostatistics ; Michele Guindani, University of California, Irvine ; Chaan Ng, The University of Texas MD Anderson C ; Brian P. Hobbs, The University of Texas MD Anderson Cancer Center
11:30 AM	Efficient Multivariate Entropy Estimation Via k-Nearest Neighbour Distances — Thomas Berrett, University of Cambridge
11:35 AM	Inference in a Hidden Markov Model with Log-Concave Emission Densities — Nathalie Akakpo, University Pierre and Marie Curie, Paris, France
11:40 AM	Enhancing Power of Case-Control Studies by Using Prevalent Cases — Marlena Maziarz, National Cancer Institute ; Jing Qin, National Institute of Allergy and Infectious Diseases ; Ruth Pfeiffer , National Cancer Institute, NIH, HHS
11:45 AM	Testing the Adequacy of Linear Mixed Effects Models — Stephanie Chen, North Carolina State University ; Luo Xiao, North Carolina State University ; Ana-Maria Staicu, North Carolina State University, Department of Statistics
11:50 AM	Floor Discussion

166	Mon, 7/31/2017, 10:30 AM - 12:20 PM	CC-330
New Developments in High-Dimensional Statistics — Contributed Papers
IMS
Chair(s): Yen-Chi Chen, University of Washington
10:35 AM	High-Dimensional Propensity Score via Covariate Balancing — Yang Ning, Cornell University ; Sida Peng, Cornell University ; Kosuke Imai, Princeton University
11:05 AM	Bootstrapping Spectral Statistics in High Dimensions — Miles Lopes, UC Davis ; Alexander Aue, University of California, Davis ; Andrew Blandino, UC Davis
11:20 AM	Adaptive Sparse Estimation with Side Information — Trambak Banerjee, USC ; Gourab Mukherjee, University of Southern California ; Wenguang Sun, University of Southern California
11:35 AM	Conditional Means of Low-Dimensional Projections from High-Dimensional Data: Explicit Error Bounds — Ivana Milovic, University of Vienna ; Hannes Leeb, University of Vienna
11:50 AM	Functional Classification with Missing Data — Crystal Shaw, CSU Northridge ; Majid Mojirsheibani, CSU Northridge
12:05 PM	Embracing the Blessing of Dimensionality in Factor Models — Quefeng Li, The University of North Carolina at Chapel Hill ; Guang Cheng, Purdue ; Jianqing Fan, Princeton University ; Yuyan Wang, Princeton University

214697	Mon, 7/31/2017, 12:00 PM - 1:30 PM	H-Key Ballroom 3
IMS Editors Meetings — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director

214718	Mon, 7/31/2017, 12:30 PM - 2:00 PM	H-Peale A
Annals of Statistics Editorial Meeting — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director

201 * !	Mon, 7/31/2017, 2:00 PM - 3:50 PM	CC-336
Essential Recent Papers in Stat — Invited Papers
International Statistical Institute , Section on Statistical Graphics , IMS
Organizer(s): John E. Kolassa, Rutgers, the State University of New Jersey
Chair(s): John E. Kolassa, Rutgers, the State University of New Jersey
2:05 PM	Visualization of Robust L1PCA — Yi-Hui Zhou, North Carolina State University ; J. S. (Steve) Marron, University of North Carolina
2:35 PM	Interactive Graphics for Functional Data Analyzes — Julia Wrobel, Columbia University, Department of Biostatistics ; So-Young Park, North Carolina State University, Department of Statistics ; Ana-Maria Staicu, North Carolina State University, Department of Statistics ; Jeff Goldsmith, Columbia University
3:05 PM	Inferring Population Size: Extending the Multiplier Method to Incorporate Multiple Traits with a Likelihood-Based Approach — Vivian Meng, McGill University
3:35 PM	Floor Discussion

205	Mon, 7/31/2017, 2:00 PM - 3:50 PM	CC-311
New Direction for Model Selection in Big Data — Invited Papers
IMS
Organizer(s): Linda Zhao, University of Pennsylvania
Chair(s): Linda Zhao, University of Pennsylvania
2:05 PM	Optimal Variable Selection via Sparse Tensor Decomposition — Dong Wang, Princeton University
2:35 PM	Private False Discovery Rate Control — Weijie Su, University of Pennsylvania ; Cynthia Dwork, Harvard University ; Li Zhang, Google Inc.
3:05 PM	Variable Selection for Bilinear Regression with Matrix Covariates — Dan Yang, Rutgers University
3:35 PM	Floor Discussion

210	Mon, 7/31/2017, 2:00 PM - 3:50 PM	CC-310
Medallion Lecture II — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
Chair(s): David Donoho, Stanford University
2:05 PM	State-Space Modeling of Dynamics Processes in Neuroscience — Emery N. Brown, Massachusetts Institute of Technology
3:45 PM	Floor Discussion

212 * !	Mon, 7/31/2017, 2:00 PM - 3:50 PM	CC-323
Selective Inference — Invited Papers
IMS
Organizer(s): Emmanuel J. Candes, Stanford University
Chair(s): Emmanuel J. Candes, Stanford University
2:05 PM	Structure Adaptive Multiple Testing — Ang Li, University of Chicago ; Rina Foygel Barber, University of Chicago
2:30 PM	AdaPT: An Interactive Procedure for Multiple Testing with Side Information — William Fithian, UC Berkeley Statistics ; Lihua Lei, UC Berkeley Statistics
2:55 PM	Selective sampling after solving a convex problem — Jonathan Taylor, Stanford University
3:20 PM	Selective Inference in hierarchical high dimensional data analysis — Yoav Benjamini, Tel-Aviv University
3:45 PM	Floor Discussion

252	Mon, 7/31/2017, 3:05 PM - 3:50 PM	CC-Halls A&B
SPEED: Nonparametrics and Imaging — Contributed Poster Presentations
Section on Nonparametric Statistics , Section on Statistics in Imaging , SSC , IMS
Chair(s): Jessi Cisewski, Yale University
2:	Automatic Shape-Constrained Nonparametric Regression — Zhikun Gao, George Washington University ; Huixia Judy Wang, The George Washington University ; Yanlin Tang, School of Mathematical Sciences, Tongji University
3:	Nonparametric Modeling of Heavy-Tailed Distributions with Applications to Extreme Events — Todd Wilson, North Carolina State University ; Sujit K Ghosh, North Carolina State University
4:	Instrument Assisted Partial-Linear Single Index Regression for Errors in Variables Models with Binary Response — Qianqian Wang, University of South Carolina ; Yanyuan Ma, Penn State University ; Guangren Yang, Jinan University ; Xia Cui, Zhongshan University
6:	Estimation of Locally Stationary Spatial Processes with Application to the American Community Survey — Daniel Weinberg, U.S. Census Bureau ; Tucker McElroy, U. S. Census Bureau ; Soumendra N Lahiri, North Carolina State University
7:	A Comparison of Testing Methods in Scalar-On-Function Regression — Merve Tekbudak, North Carolina State University ; Marcela Alfaro Córdoba, North Carolina State University ; Ana-Maria Staicu, North Carolina State University, Department of Statistics ; Arnab Maity, North Carolina State University
8:	Weighted Quantile Regression Splines using Total Variation Regularization — Jae-Hwan Jhong, Korea University ; Ja-Yong Koo, Korea University
10:	Bayesian Methods for Image Texture Analysis with Applications to Cancer Radiomics — Xiao Li, University of Texas, School of Public Health, Department of Biostatistics ; Michele Guindani, University of California, Irvine ; Chaan Ng, The University of Texas MD Anderson C ; Brian P. Hobbs, The University of Texas MD Anderson Cancer Center
11:	Efficient Multivariate Entropy Estimation Via k-Nearest Neighbour Distances — Thomas Berrett, University of Cambridge
12:	Inference in a Hidden Markov Model with Log-Concave Emission Densities — Nathalie Akakpo, University Pierre and Marie Curie, Paris, France
13:	Enhancing Power of Case-Control Studies by Using Prevalent Cases — Marlena Maziarz, National Cancer Institute ; Jing Qin, National Institute of Allergy and Infectious Diseases ; Ruth Pfeiffer , National Cancer Institute, NIH, HHS
14:	Testing the Adequacy of Linear Mixed Effects Models — Stephanie Chen, North Carolina State University ; Luo Xiao, North Carolina State University ; Ana-Maria Staicu, North Carolina State University, Department of Statistics
The Speed portion will take place during Session 214529

255	Mon, 7/31/2017, 8:00 PM - 9:30 PM	CC-Ballroom I
IMS Presidential Address and Awards Ceremony — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
8:05 PM	Teaching Statistics in the Age of Data Science — Jon A. Wellner, University of Washington

214698	Mon, 7/31/2017, 9:30 PM - 11:00 PM	CC-Ballroom II
IMS Reception Following the IMS Presidential Address and Awards Ceremony — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director

265	Tue, 8/1/2017, 8:30 AM - 10:20 AM	CC-309
New Directions in Statistical Network Analysis — Invited Papers
Section on Statistical Learning and Data Science , IMS , Section on Nonparametric Statistics
Organizer(s): Liza Levina, University of Michigan
Chair(s): Liza Levina, University of Michigan
8:35 AM	Structured Shrinkage for Network Regression — Peter Hoff, Duke University
9:00 AM	Prediction Models for Network-Linked Data — Ji Zhu, University of Michigan
9:25 AM	Network modelling of topological domains using Hi-C data — Rachel Wang ; Purnamrita Sarkar, University of Texas, Austin ; Oana Ursu, Stanford University ; Anshul Kundaje, Stanford University ; Peter Bickel, University of California, Berkeley
9:50 AM	Discussant: Edoardo M. Airoldi, Harvard University
10:15 AM	Floor Discussion

268 * !	Tue, 8/1/2017, 8:30 AM - 10:20 AM	CC-349
A Unifying Theme for Interpretable Information Extraction from Data: The Stability Principle — Invited Papers
IMS , Section on Statistical Learning and Data Science
Organizer(s): Bin Yu, University of California, Berkeley
Chair(s): Anru Zhang, University of Wisconsin-Madison
8:35 AM	Three Principles for Data Science: Predictability, Stability and Computability — Bin Yu, University of California, Berkeley
9:00 AM	Stability, Uncertainty, and Bayesian Learning — Chris Holmes, University of Oxford
9:25 AM	Max-Information, Differential Privacy, and Post-Selection Hypothesis Testing — Ryan Rogers, University of Pennsylvania ; Aaron Roth, University of Pennsylvania ; Adam Smith, Pennsylvania State University ; Om Thakkar, Penn State
9:50 AM	The Central Role of Stability in Causal Inference — Peng Ding, University of California, Berkeley
10:15 AM	Floor Discussion

272 !	Tue, 8/1/2017, 8:30 AM - 10:20 AM	CC-350
Modern Statistical Inference — Invited Papers
IMS
Organizer(s): Harrison H. Zhou, Yale University
Chair(s): Harrison H. Zhou, Yale University
8:35 AM	Optimal hypothesis testing for stochastic block models with growing degrees — Debapratim Banerjee, University of Pennsylvania ; Zongming Ma, University of Pennsylvania
9:05 AM	Linear Predictors for Semi-Supervised Regression — Lawrence D. Brown, University of Pennsylvania
9:35 AM	Generalized Cp (GCP) for Realistic Out-Of-Sample Prediction — Linda Zhao, University of Pennsylvania
10:05 AM	Floor Discussion

274	Tue, 8/1/2017, 8:30 AM - 10:20 AM	CC-310
Medallion Lecture III — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
Chair(s): Moulinath Banerjee, University of Michigan
8:35 AM	Coverage of Nonparametric Credible Sets — Subhashis Ghoshal, North Carolina State University
10:15 AM	Floor Discussion

306	Tue, 8/1/2017, 10:30 AM - 12:20 PM	CC-328
Causal Inference — Invited Papers
IMS
Organizer(s): Peter Bühlmann, ETH Zurich
Chair(s): Dylan Small, University of Pennsylvania
10:35 AM	Inferring Causal Effects with Invalid Instruments in Mendelian Randomization — Hyunseung Kang, Economics, Stanford Graduate School of Business, Stanford University
11:05 AM	Causal Structure Learning in High-Dimensional Settings — Preetam Nandy, University of Pennsylvania
11:35 AM	Causal structure learning for multivariate point processes — Niels Richard Hansen, University of Copenhagen
12:05 PM	Floor Discussion

309 *	Tue, 8/1/2017, 10:30 AM - 12:20 PM	CC-331/332
Statistical Topics in Precision Medicine — Invited Papers
IMS , ENAR , Section on Statistical Learning and Data Science
Organizer(s): Heping Zhang, Yale University School of Public Health
Chair(s): Heping Zhang, Yale University School of Public Health
10:35 AM	New Adaptive Designs of Clinical Trial for Precision Medicine — Feifang Hu, George Washington University
11:00 AM	Individualized Fusion Learning (IFusion) with Applications to Personalized Inference — Minge Xie, Rutgers University ; Jieli Shen, Rutgers University ; Regina Liu, Rutgers University
11:25 AM	Statistical Machine Learning and Precision Medicine — Michael Lawson, University of North Carolina at Chapel Hill ; Michael R Kosorok, University of North Carolina at Chapel Hill
11:50 AM	Hypothesis testings on high-dimensional individualized treatment rules — Young-Geun Choi, Fred Hutchinson Cancer Research Center ; Yang Ning, Cornell University ; Yingqi Zhao, Fred Hutchinson Cancer Research Center
12:15 PM	Floor Discussion

310	Tue, 8/1/2017, 10:30 AM - 12:20 PM	CC-336
Advances and Novel Problems in Flexible Analysis of Clustered Data with Complex Structures — Invited Papers
Section on Nonparametric Statistics , Korean International Statistical Society , IMS
Organizer(s): Lan Wang, University of Minnesota
Chair(s): Lan Wang, University of Minnesota
10:35 AM	Flexible parametric approach to classical measurement error variance estimation without auxiliary data — Ingrid Van Keilegom, ORSTAT, KU LEUVEN
11:00 AM	Flexible Bayesian Additive Joint Models — Meike Köhler, Helmholtz Zentrum München ; Nikolaus Umlauf, Universität Innsbruck ; Sonja Greven, Ludwig-Maximilians-Universität München
11:25 AM	Analysis of Clustered Complex Design Data: Propensity Score Matching — Mi-Ok Kim, UCSF
11:50 AM	A Simple and Adaptive Two-Sample Test in High Dimensions — Jin-Ting Zhang, National University of Singapore ; Jin Guo, National University of Singapore ; Bu Zhou, National University of Singapore ; Ming-Yen Cheng, National Taiwan University
12:15 PM	Floor Discussion

314	Tue, 8/1/2017, 10:30 AM - 12:20 PM	CC-329
Recent Advances in High-Dimensional Inferences — Invited Papers
IMS , International Chinese Statistical Association , Section on Statistical Learning and Data Science
Organizer(s): Ming Yuan, University of Wisconsin
Chair(s): Ming Yuan, University of Wisconsin
10:35 AM	Overlapping clustering with LOVE — Florentina Bunea, Cornell
11:00 AM	Adaptive Prediction in Additive Models — Cun-Hui Zhang, Rutgers University
11:25 AM	Rate-Optimal Perturbation Bounds for Singular Subspaces with Applications to High-Dimensional Data Analysis — Tony Cai, University of Pennsylvania ; Anru Zhang, University of Wisconsin-Madison
11:50 AM	Robust Covariate-Adjusted Multiple Testing — Jianqing Fan, Princeton University ; Wen-Xin Zhou, Princeton University ; Koushiki Bose, Princeton University ; Han Liu, Princeton University
12:15 PM	Floor Discussion

332	Tue, 8/1/2017, 10:30 AM - 12:20 PM	CC-322
SPEED: Section on Bayesian Statistical Science — Contributed Speed
Section on Bayesian Statistical Science , IMS
Chair(s): Nanhua Zhang, Cincinnati Children's Hospital Medical Center
10:35 AM	Bayesian Models for Automatic Landmark Detection on Elastic Curves — Justin Strait, Department of Statistics, The Ohio State University ; Oksana A Chkrebtii, The Ohio State University ; Sebastian Kurtek, The Ohio State University
10:40 AM	Adaptive Bayesian Modeling and Prediction of Patient Accrual with Varying Activation Time in Multicenter Clinical Trials — Junhao Liu, University of Kansas Medical Center ; Yu Jiang, School of Public Health, University of Memphis ; Jo Wick, University of Kansas Medical Center ; Byron Gajewski, Department of Biostatistics, University of Kansas Medical Center
10:45 AM	A Bayesian Approach for the Segmentation of Series Corrupted by a Functional Part — Cristian Meza, CIMFAV-Universidad de Valparaíso ; Meili Baragatti, SupAgro-INRA ; Karine Bertin, CIMFAV-Universidad de Valparaíso ; Emilie Lebarbier, AgroParisTech
10:50 AM	A Bayesian Race Model for Response Times Under Cyclic Stimulus Discriminability — Deborah Kunkel, The Ohio State University ; Kevin Potter, University of Massachusetts ; Trisha Van Zandt, The Ohio State University ; Peter F Craigmile, The Ohio State University ; Mario Peruggia, The Ohio State University
10:55 AM	Partioning Priors for Spatiotemporal Multiscale Models — Andrew Hoegh, Montana State University
11:10 AM	A Bayesian Sequential Design with Adaptive Randomization for Two-Sided Hypothesis Tests — Qingzhao Yu, Louisiana State University Health Sciences Center ; Lin Zhu, Louisiana State University Health Sciences Center ; Han Zhu, Pharmaceutical Product Development, Inc.
11:15 AM	Bayesian Inference about the Directional Brain Network Modeled by Damped Harmonic Oscillators for Intracranial EEG Data — Yinge Sun, University of Virginia ; Tingting Zhang, University of Virginia ; Qiannan Yin, University of Virginia ; Brian Scott Caffo, Johns Hopkins ; Dana Boatman-Reich, Johns Hopkins University
11:30 AM	Hyperparameter Selection for the Latent Dirichlet Allocation Model — Wei Xia, University of Florida ; Hani Doss, University of Florida
11:45 AM	Bayesian Clustering on Stiefel Manifolds — Ritendranath Mitra ; Subhajit Sengupta, NorthShore University Health System ; Subhadip Pal, University of Louisville
11:50 AM	Marginalization Over Uncertainty in Propensity Score Design Using Bayesian Analysis — Shirley Liao ; Corwin Zigler, Harvard University
11:55 AM	Dynamic Posterior Exploration for Simultaneous Variable and Covariance Selection with Spike and Slab Priors — Sameer Kirtikumar Deshpande, The Wharton School ; Veronika Rockova, University of Chicago ; Edward I. George, Wharton, University of Pennsylvania
12:10 PM	Multi-Way Interacting Regression via Factorization Machines — Mikhail Yurochkin ; Long Nguyen, University of Michigan ; Nikolaos Vasiloglou, Infor
12:15 PM	Geometric Ergodicity of Gibbs Samplers in Bayesian Penalized Regression Models — Dootika Vats, University of Minnesota

339	Tue, 8/1/2017, 10:30 AM - 12:20 PM	CC-330
Model-Fitting, Likelihood-Based Inference, and Their Applications — Contributed Papers
IMS
Chair(s): Grace Li, Eli Lilly and Company
10:35 AM	On the Properties of the Gradient of Log Empirical Likelihood — Sanjay Chaudhuri, National University of Singapore
10:50 AM	Robust Tests Using a Divergence Measure — Abhijit Mandal, Wayne State University ; Ayanendranath Basu, Indian Statistical Institute ; Leandro Pardo, Complutense University of Madrid ; Nirian Martin, Complutense University of Madrid
11:05 AM	Different Paradigms of Interpretation for Forensic Value of Evidence Quantification — Danica Ommen, South Dakota State University ; Christopher Saunders, South Dakota State University ; Reinoud Stoel, Netherlands Forensic Institute ; Peter Vergeer, Netherlands Forensic Institute
11:20 AM	Robustness of Lognormal Confidence Regions for Means of Symmetric Positive Matrices — Benoit Ahanda, Texas Tech University ; Daniel E Osborne, Florida A&M University ; Leif Ellingson, Texas Tech University
11:50 AM	Floor Discussion

354	Tue, 8/1/2017, 10:30 AM - 12:20 PM	CC-Halls A&B
Contributed Poster Presentations: IMS — Contributed Poster Presentations
IMS
Chair(s): Jessi Cisewski, Yale University
28:	Exponentiated Generalized Pareto Distribution: Properties and Applications Towards Extreme Value Theory — Se Yoon Lee, Texas A&M University ; Joseph H. T. Kim, Yonsei University
29:	Properties of Some Modern Measures of Dependence — Mary Elvi Paler, University of Wisconsin-Platteville ; Maria Rizzo, Bowling Green State University
30:	Plausibility Regions on the Parameters of Skew Normal Distributions Based on Inferential Models — Xiaonan Zhu, New Mexico State University ; Tonghui Wang, New Mexico State University ; Baokun Li, Southwestern University of Finance and Economy, P. R. China
31:	Minimax Estimation of Large Precision Matrices with Bandable Cholesky Factor — Yu Liu, University of Pittsburgh ; Zhao Ren, University of Pittsburg
32:	Incomplete U-Processes for Forensic Sufficiency Studies in Questioned Document Examination — Cami Fuglsby, South Dakota State University ; Christopher Saunders, South Dakota State University

214699	Tue, 8/1/2017, 12:30 PM - 2:00 PM	H-Key Ballroom 10
IMS Council Meeting — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director

214700	Tue, 8/1/2017, 2:00 PM - 2:30 PM	H-Key Ballroom 10
IMS Business Meeting — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director

380	Tue, 8/1/2017, 2:00 PM - 3:50 PM	CC-328
Recent Advances in High-Dimensional Statistics and Computational Methods — Invited Papers
IMS , Section on Statistical Learning and Data Science
Organizer(s): Yin Xia, Fudan University
Chair(s): Yin Xia, Fudan University
2:05 PM	SMART: Simultaneous Multistage Adaptive Ranking and Thresholding for Sparse Signal Recovery — Wenguang Sun, University of Southern California ; Weinan Wang, University of Southern California
2:30 PM	RESTRICTED STRONG CONVEXITY IMPLIES WEAK SUBMODULARITY — Sahand Negahban, Yale University ; Ethan Elenberg, UT Austin ; Rajiv Khanna, UT Austin ; Alex Dimakis, UT Austin
2:55 PM	Interactive Visualization and Fast Computation of the Solution Path for Convex Clustering and Biclustering — John Nagorski, Rice University ; Genevera I. Allen, Rice University
3:20 PM	Identifiability and Inference of Causal Effects with High-Dimensional and Invalid Instruments — Changjing Wu, Peking University ; Minghua Deng, Peking University ; Wei Lin, Peking University
3:45 PM	Floor Discussion

387	Tue, 8/1/2017, 2:00 PM - 3:50 PM	CC-Ballroom I
Medallion Lecture IV — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
Chair(s): David Dunson, Duke University
2:05 PM	Probabilistic Numerical Computation: A Role for Statisticians in Numerical Analysis? — Mark Girolami, Imperial College London
3:45 PM	Floor Discussion

388 !	Tue, 8/1/2017, 2:00 PM - 3:50 PM	CC-329
Random Matrices and Applications — Invited Papers
IMS , Section on Statistical Learning and Data Science
Organizer(s): Iain M Johnstone, Stanford Universty
Chair(s): Iain M Johnstone, Stanford Universty
2:05 PM	Free Component Analysis — Raj Rao Nadakuditi, University of Michigan
2:30 PM	High-Dimensional Cointegration Analysis — Alexei Onatski, University of Cambridge
2:55 PM	On Structure Testing for Component Covariance Matrices of a High-Dimensional Mixture — Jianfeng YAO, The University of Hong Kong ; Weiming Li, Shanghai University of Finance and Economics
3:20 PM	SHARP DETECTION in PCA UNDER CORRELATIONS — Edgar Dobriban, Stanford University
3:45 PM	Floor Discussion

403	Tue, 8/1/2017, 2:00 PM - 3:50 PM	CC-325
Selected Topics on Hypothesis Testing and Statistical Inference — Contributed Papers
IMS , Section on Statistics in Genomics and Genetics , Section on Statistical Learning and Data Science
Chair(s): Quefeng Li, The University of North Carolina at Chapel Hill
2:05 PM	A Neighborhood Hypothesis Test for Functional Data with an Application to Ecological Data — Leif Ellingson, Texas Tech University ; Dhanamalee Bandara, Texas Tech University ; Souparno Ghosh, Texas Tech University
2:20 PM	Testing for Model Adequacy in Censored Location-Scale Families — Sundarraman Subramanian, New Jersey Institute of Technology
2:35 PM	Nonparametric Inference via Bootstrapping the Debiased Estimator — Yen-Chi Chen, University of Washington
2:50 PM	A Higher Order Criticism of Higher Criticism — Thomas Porter, The University of Sydney ; Michael Stewart, The University of Sydney
3:05 PM	A Doubly Adaptive Inferential Method for Monotone Graph Invariants — Junwei Lu, Princeton University ; Matey Neykov, Princeton University ; Han Liu, Princeton University
3:20 PM	Hypothesis Testing for Simultaneous Variable Clustering and Correlation Network Estimation, with Application to Gene Co-Expression Networks — Kevin Lin, Carnegie Mellon University, Statistics Department ; Junwei Lu, Princeton University ; Han Liu, Princeton University ; Kathryn Roeder, Carnegie Mellon University
3:35 PM	Using Phylogenetic Models for Quantitative Trait Mapping with Multiple Loci — Katherine Thompson, University of Kentucky ; Catherine Linnen, University of Kentucky

422	Tue, 8/1/2017, 2:00 PM - 2:45 PM	CC-Halls A&B
SPEED: Section on Bayesian Statistical Science — Contributed Poster Presentations
Section on Bayesian Statistical Science , IMS
Chair(s): Jessi Cisewski, Yale University
1:	Bayesian Models for Automatic Landmark Detection on Elastic Curves — Justin Strait, Department of Statistics, The Ohio State University ; Oksana A Chkrebtii, The Ohio State University ; Sebastian Kurtek, The Ohio State University
2:	Adaptive Bayesian Modeling and Prediction of Patient Accrual with Varying Activation Time in Multicenter Clinical Trials — Junhao Liu, University of Kansas Medical Center ; Yu Jiang, School of Public Health, University of Memphis ; Jo Wick, University of Kansas Medical Center ; Byron Gajewski, Department of Biostatistics, University of Kansas Medical Center
3:	A Bayesian Race Model for Response Times Under Cyclic Stimulus Discriminability — Deborah Kunkel, The Ohio State University ; Kevin Potter, University of Massachusetts ; Trisha Van Zandt, The Ohio State University ; Peter F Craigmile, The Ohio State University ; Mario Peruggia, The Ohio State University
6:	A Bayesian Sequential Design with Adaptive Randomization for Two-Sided Hypothesis Tests — Qingzhao Yu, Louisiana State University Health Sciences Center ; Lin Zhu, Louisiana State University Health Sciences Center ; Han Zhu, Pharmaceutical Product Development, Inc.
7:	Bayesian Inference about the Directional Brain Network Modeled by Damped Harmonic Oscillators for Intracranial EEG Data — Yinge Sun, University of Virginia ; Tingting Zhang, University of Virginia ; Qiannan Yin, University of Virginia ; Brian Scott Caffo, Johns Hopkins ; Dana Boatman-Reich, Johns Hopkins University
9:	Hyperparameter Selection for the Latent Dirichlet Allocation Model — Wei Xia, University of Florida ; Hani Doss, University of Florida
11:	Multi-Way Interacting Regression via Factorization Machines — Mikhail Yurochkin ; Long Nguyen, University of Michigan ; Nikolaos Vasiloglou, Infor
12:	Geometric Ergodicity of Gibbs Samplers in Bayesian Penalized Regression Models — Dootika Vats, University of Minnesota
13:	A Bayesian Approach for the Segmentation of Series Corrupted by a Functional Part — Cristian Meza, CIMFAV-Universidad de Valparaíso ; Meili Baragatti, SupAgro-INRA ; Karine Bertin, CIMFAV-Universidad de Valparaíso ; Emilie Lebarbier, AgroParisTech
14:	Marginalization Over Uncertainty in Propensity Score Design Using Bayesian Analysis — Shirley Liao ; Corwin Zigler, Harvard University
15:	Dynamic Posterior Exploration for Simultaneous Variable and Covariance Selection with Spike and Slab Priors — Sameer Kirtikumar Deshpande, The Wharton School ; Veronika Rockova, University of Chicago ; Edward I. George, Wharton, University of Pennsylvania
16:	Partioning Priors for Spatiotemporal Multiscale Models — Andrew Hoegh, Montana State University
18:	Bayesian Clustering on Stiefel Manifolds — Ritendranath Mitra ; Subhajit Sengupta, NorthShore University Health System ; Subhadip Pal, University of Louisville
The Speed portion will take place during Session 214517

426	Tue, 8/1/2017, 4:00 PM - 5:50 PM	CC-Ballroom I
Wald Lecture I — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
Chair(s): Tony Cai, University of Pennsylvania
4:05 PM	What's Happening in Selective Inference I? — Emmanuel J. Candes, Stanford University
5:45 PM	Floor Discussion

214701	Wed, 8/2/2017, 7:30 AM - 9:00 AM	H-Poe B
Statistics Surveys Editors Meeting — Other ICW
IMS
Organizer(s): Elyse Gustafson, IMS Executive Director

436	Wed, 8/2/2017, 8:30 AM - 10:20 AM	CC-337
Modern Change Point Problems — Invited Papers
IMS
Organizer(s): Richard J. Samworth, Statistical Laboratory, University of Cambridge
Chair(s): Richard J. Samworth, Statistical Laboratory, University of Cambridge
8:35 AM	Multiple change-point detection via multiscale MOSUM procedure with localised pruning — Haeran Cho, University of Bristol
9:00 AM	Recent Advances in Multiple Change-Point Detection — Piotr Fryzlewicz, London School of Economics ; Yining Chen, London School of Economics ; Rafal Baranowski, London School of Economics
9:25 AM	Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers — Veeranjaneyulu Sadhanala, Carnegie Mellon University ; Yu-Xiang Wang, Carnegie Mellon University ; Ryan Tibshirani, Carnegie Mellon University
9:50 AM	Floor Discussion

442	Wed, 8/2/2017, 8:30 AM - 10:20 AM	CC-338
Model-Based Statistical Analysis of Network Data — Invited Papers
IMS
Organizer(s): Zongming Ma, University of Pennsylvania
Chair(s): Zongming Ma, University of Pennsylvania
8:35 AM	Random Networks, Graphical Models, and Exchangeability — Alessandro Rinaldo, Carnegie Mellon University ; Steffen Lilholt Lauritzen, University of Copenhagen ; Kayvan Sadeghi, University of Cambridge
9:00 AM	Community Detection in Multi-Relational Data Through Multi-Layer Stochastic Blockmodel — Yuguo Chen, University of Illinois at Urbana-Champaign
9:25 AM	Statistical and Computational Guarantees of Lloyd's Algorithm and Its Variants — Yu Lu, Yale University ; Harrison H. Zhou, Yale University
9:50 AM	Estimating the number of connected components of large graphs based on subgraph sampling — Yihong Wu, Yale University
10:15 AM	Floor Discussion

444	Wed, 8/2/2017, 8:30 AM - 10:20 AM	CC-310
Medallion Lecture V — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
Chair(s): Edward I. George, Wharton, University of Pennsylvania
8:35 AM	On the Semiparametric Bernstein-Von Mises Theorem in Regular and Nonregular Models — Judith N. Rousseau, Université Paris Dauphine
10:15 AM	Floor Discussion

446 * !	Wed, 8/2/2017, 8:30 AM - 10:20 AM	CC-328
Prediction vs. Inference in Personalized Medicine — Invited Papers
Mental Health Statistics Section , IMS , Section on Risk Analysis
Organizer(s): Booil Jo, Stanford University
Chair(s): Elizabeth Stuart, Johns Hopkins University
8:35 AM	Personalizing Mobile Health Interventions — Susan A Murphy, University of Michigan
9:00 AM	Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods — Hemant Ishwaran, University of Miami
9:25 AM	Discussant: Tyler J. VanderWeele, Harvard University
9:45 AM	Discussant: Xiao-Li Meng, Harvard University
10:05 AM	Floor Discussion

477 *	Wed, 8/2/2017, 10:30 AM - 12:20 PM	CC-336
Bayesian Methods for High-Dimensional Inference — Invited Papers
IMS , Section on Bayesian Statistical Science , International Society for Bayesian Analysis (ISBA) , Section on Statistical Learning and Data Science
Organizer(s): David Dunson, Duke University
Chair(s): David Dunson, Duke University
10:35 AM	Clustering High-Dimensional Data Using Summary Statistics — Valen Johnson, Texas A&M University
11:00 AM	Bayesian Partition Logistic Regression Models — Jun Liu, Harvard University
11:25 AM	High-Dimensional Linear Regression via the R-Squared Induced Dirichlet Decomposition Prior — Howard Bondell, NC State University ; Brian Reich, NCSU ; Yan Dora Zhang, Johns Hopkins
11:50 AM	Nonparametric Maximum Likelihood Approximate Message Passing — Lee Dicker, Rutgers University ; Ruijun Ma, Rutgers University
12:15 PM	Floor Discussion

478	Wed, 8/2/2017, 10:30 AM - 12:20 PM	CC-330
Online Machine Learning for Prediction and Sequential Decision Making — Invited Papers
IMS , Association for the Advancement of Artificial Intelligence , Institute for Operations Research and the Management Sciences , Section on Statistical Learning and Data Science
Organizer(s): Susan A Murphy, University of Michigan
Chair(s): Susan A Murphy, University of Michigan
10:35 AM	A New Approach to Online Prediction — Alexander Rakhlin, University of Pennsylvania
11:00 AM	Online Decision-Making with High-Dimensional Covariates — Hamsa Bastani, Stanford University ; Mohsen Bayati, Stanford University
11:25 AM	Regret Bounds for Adaptive Control of Linear Quadratic Systems — Mohamad Kazem Shirani Faradonbeh, University of Michigan ; Ambuj Tewari, University of Michigan ; George Michailidis, University of Florida
11:50 AM	Improved Strongly Adaptive Online Learning Using Coin Betting — Rebecca Willett, University of Wisconsin-Madison ; Kwang-Sung Jun, University of Wisconsin-Madison ; Francesco Orabona, Stony Brook University ; Stephen Wright, University of Wisconsin-Madison
12:15 PM	Floor Discussion

479 * !	Wed, 8/2/2017, 10:30 AM - 12:20 PM	CC-338
Statistical Analysis of Complex Imaging Data — Invited Papers
Section on Nonparametric Statistics , IMS , Section on Statistics in Imaging , ENAR
Organizer(s): Dehan Kong, University of Toronto
Chair(s): Dehan Kong, University of Toronto
10:35 AM	JIVE Integration of Behavioral and fMRI Data — J. S. (Steve) Marron, University of North Carolina ; Benjamin Risk, SAMSI, Department of Biostatistics and Bioinformatics, Emory University ; Qunqun Yu, UNC - Statistics & OR
11:00 AM	Exploratory and Data Visualization Methods for High-Dimensional Brain Signals — Hernando Ombao, KAUST and UC Irvine ; Yuxiao Wang, University of California, Irvine ; Chee-Ming Ting, KAUST
11:25 AM	Am I My Connectome? Fingerprinting with Repeated Resting State Functional MRI Data — Brian Scott Caffo, Johns Hopkins ; Zeyi Wang, Johns Hopkins ; Ciprian M Crainiceanu, Johns Hopkins University ; Martin Lindquist, Johns Hopkins University ; Jim Pekar, Johns Hopkins ; Joshua Vogelstein, Johns Hopkins ; Haris Sair, Johns Hopkins
11:50 AM	Statistical Analysis of Registration and Registered Imaging Data — John AD Aston, University of Cambridge ; Eardi Lila, University of Cambridge
12:15 PM	Floor Discussion

486	Wed, 8/2/2017, 10:30 AM - 12:20 PM	CC-Ballroom I
Wald Lecture II — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
Chair(s): Judith N. Rousseau, Université Paris Dauphine
10:35 AM	What's Happening in Selective Inference II? — Emmanuel J. Candes, Stanford University
12:15 PM	Floor Discussion

487 *	Wed, 8/2/2017, 10:30 AM - 12:20 PM	CC-326
Design and Analysis of Computer Experiments for Complex Systems — Invited Papers
Section on Physical and Engineering Sciences , Section on Statistical Computing , IMS
Organizer(s): Ying Hung
Chair(s): Ying Hung
10:35 AM	Replication or exploration? Sequential design for stochastic simulation experiments. — Robert Gramacy, Virginia Tech Department of Statistics ; Bickael Binois, The University of Chicago ; Mike Ludkovski, University of California, Santa Barbara
11:00 AM	Analysis of dimension reduction in Gaussian process regression — Minyong Lee, Stanford University ; Art Owen, Stanford University
11:25 AM	Stabilizing Gradient Enhanced Emulators with Sparsity Constraints — Peter Qian, University of Wisconsin-Madison ; Jared Huling, University of Wisconsin-Madison
11:50 AM	Sequential learning of deformation models in additive manufacturing through calibration of simulation models — Tirthankar Dasgupta, Rutgers University ; Ying Hung
12:15 PM	Floor Discussion

510	Wed, 8/2/2017, 10:30 AM - 12:20 PM	CC-322
New Developments in Time Series Analysis and Change Point Detection — Contributed Papers
IMS
Chair(s): Katherine Thompson, University of Kentucky
10:35 AM	Implicit Multi-Layer Network for Time Series Data — Brandon Park ; Anand N. Vidyashankar, George Mason University ; Tucker McElroy, U. S. Census Bureau
10:50 AM	A Time Series Model for Boolean Random Sets — Khalil Shafie, University of Northern Colorado ; Mostafa Zahed, University of Northern Colorado
11:05 AM	Change Point Estimation in a Dynamic Stochastic Block Model — Monika Bhattacharjee, Informatics Institute, University of Florida ; George Michailidis, University of Florida ; Moulinath Banerjee, University of Michigan
11:20 AM	Post-Selection Inference for Segmentation Methods in Changepoint Detection — Sangwon Hyun, Carnegie Mellon University ; Kevin Lin, Carnegie Mellon University, Statistics Department ; Max G'sell, Carnegie Mellon University ; Ryan Tibshirani, Carnegie Mellon University
11:35 AM	Detecting Discontinuities in a Regression Curve — Cidambi Srinivasan, University of Kentucky ; Sisheng Liu, University of Kentucky ; Richard Charnigo, University of Kentucky
11:50 AM	Fitting a Stochastic Differential Equation Model to Eye Tracking Data — Yunlong Nie, Simon Fraser University
12:05 PM	Estimation of GARCH Process by Empirical Likelihood — Kenichiro Tamaki, Waseda University

553 !	Wed, 8/2/2017, 2:00 PM - 3:50 PM	CC-331/332
Bayesian Nonparametrics — Invited Papers
IMS
Organizer(s): Judith N. Rousseau, Université Paris Dauphine
Chair(s): Judith N. Rousseau, Université Paris Dauphine
2:05 PM	Application of Sparse Exchangeable Graphs to Infinite Latent Feature Modeling — Zacharie Naulet, University of Toronto
2:35 PM	Bayesian Quantile Regression via Restricted Likelihood — Steven MacEachern, The Ohio State University
3:05 PM	Singularity Structure of Parameter Space and Posterior Contraction in Finite Mixture Models — Long Nguyen, University of Michigan ; Nhat Ho, University of Michigan
3:35 PM	Floor Discussion

560	Wed, 8/2/2017, 2:00 PM - 3:50 PM	CC-Ballroom I
Annals of Statistics Special Invited Session: Selected Papers — Invited Papers
IMS
Organizer(s): Edward I. George, Wharton, University of Pennsylvania
Chair(s): Edward I. George, Wharton, University of Pennsylvania
2:05 PM	Higher Order Influence Functions and Minimax Estimation of Nonlinear Functionals — James Robins, Harvard University ; Aad van der Vaart, Universiteit Leiden ; Eric Tchetgen Tchetgen, Harvard University ; lingling li, sanofi genzyme ; rajarshi mukherjee, stanford
2:30 PM	Minimax Rates of Community Detection in Stochastic Block Models — Harrison H. Zhou, Yale University ; Anderson Zhang, Yale University
2:55 PM	Global Rates of Convergence in Log-Concave Density Estimation — Richard J. Samworth, Statistical Laboratory, University of Cambridge ; Arlene Kyoung Hee Kim, Sungshin Women's University
3:20 PM	A New Perspective on Boosting in Linear Regression via Modern Optimization — Rahul Mazumder, Massachusetts Institute of Technology ; Robert Freund, Massachusetts Institute of Technology ; Paul Grigas, University of California, Berkeley
3:45 PM	Floor Discussion

569 !	Wed, 8/2/2017, 2:00 PM - 3:50 PM	CC-330
Recent Advances in Predictive Inference — Topic Contributed Papers
IMS
Organizer(s): Gourab Mukherjee, University of Southern California
Chair(s): Pingshou Zhong, Michigan State University
2:05 PM	Predictive Density Estimation for Multivariate Normal and Spherically Symmetric Densities — Eric Marchand, Universite De Sherbrooke
2:25 PM	On Sparse Bayes Predictive Density Estimates — Gourab Mukherjee, University of Southern California
2:45 PM	Harmonic Bayesian Prediction Under Alpha-Divergence — Yuzo Maruyama, The University of Tokyo
3:05 PM	Shrinkage Priors for Poisson-Based Models and Their Applications — Fumiyasu Komaki, The University of Tokyo
3:25 PM	Predictive Inference for Regression — Maxwell Grazier G'Sell, Carnegie Mellon University
3:45 PM	Floor Discussion

591	Thu, 8/3/2017, 8:30 AM - 10:20 AM	CC-309
On Shape-Constrained Estimation and Inference — Invited Papers
IMS , Section on Nonparametric Statistics
Organizer(s): Bodhisattva Sen, Columbia University
Chair(s): Adityanand Guntuboyina, UC Berkeley
8:35 AM	Estimation of a Convex Density Support Using Contaminated Data — Victor-Emmanuel Brunel, MIT
9:05 AM	Efficient Estimation in Convex Single Index Models — Rohit Patra, University of Florida
9:35 AM	Isotonic Regression in general dimensions — Sabyasachi Chatterjee, University of Chicago
10:05 AM	Discussant: Bodhisattva Sen, Columbia University

598	Thu, 8/3/2017, 8:30 AM - 10:20 AM	CC-310
Wald Lecture III — Invited Papers
IMS
Organizer(s): Tony Cai, University of Pennsylvania
Chair(s): Eric Kolaczyk, Boston University
8:35 AM	What's Happening in Selective Inference III? — Emmanuel J. Candes, Stanford University
10:15 AM	Floor Discussion

612 * !	Thu, 8/3/2017, 8:30 AM - 10:20 AM	CC-306
New Challenges in High-Dimensional Statistical Inference — Topic Contributed Papers
IMS , Section on Statistics in Genomics and Genetics , Section on Statistical Learning and Data Science
Organizer(s): Lingzhou Xue, The Pennsylvania State University
Chair(s): Zheng Ke, University of Chicago
8:35 AM	Optimal Estimation of Co-Heritability in High-Dimensional Linear Models — Zijian Guo, University of Pennsylvania, Wharton School ; Wangjie Wang , National University of Singapore ; Tony Cai, University of Pennsylvania ; Hongzhe Li, University of Pennsylvania
8:55 AM	Some New Insights in High-Dimensional Independence Tests — Danning Li, Jilin University
9:15 AM	Pairwise Difference Estimation of High Dimensional Partially Linear Model — Fang Han, University of Washington ; Zhao Ren, University of Pittsburg ; Yuxin Zhu, Johns Hopkins University
9:35 AM	Homogeneity Test of Covariance Matrices with High-Dimensional Longitudinal Data — Pingshou Zhong, Michigan State University ; Runze Li, The Pennsylvania State University
9:55 AM	Floor Discussion

622	Thu, 8/3/2017, 8:30 AM - 10:20 AM	CC-304
Probability Distribution Theory and Their Applications — Contributed Papers
IMS
Chair(s): Wenguang Sun, University of Southern California
8:35 AM	Parameter Inference for a Three-Parameter Generalized Birnbaum- Saunders Distribution — Naijun Sha, University of Texas At El Paso
8:50 AM	Two Multivariate Generalized Beta Families — James McDonald, Brigham Young University
9:05 AM	On an Efficient Estimator of Exponential Parameter and Its Distributional Fit — Tanweer Shapla, Eastern Michigan University ; Khairul Islam, Eastern Michigan University
9:20 AM	Skew-Normal Approximation to the Hypergeometric Distribution — Jose Sanqui, Appalachian State University ; Dong Won Jung, Appalachian State University
9:35 AM	A Bivariate Asymmetric Laplace Distribution — Matthew Arvanitis
9:50 AM	Some Inferences on Loglogistic Distribution — Mohammad Ahsanullah, Rider University
10:05 AM	Floor Discussion

631	Thu, 8/3/2017, 10:30 AM - 12:20 PM	CC-308
Recent Developments in Statistical Inference Using Distance Correlation and Related Dependence Metrics — Invited Papers
Section on Nonparametric Statistics , IMS , International Chinese Statistical Association
Organizer(s): Xiaofeng Shao, University of Illinois, At Urbana-Champaign
Chair(s): Xiaofeng Shao, University of Illinois, At Urbana-Champaign
10:35 AM	Applications of Distance Correlation to Time Series — Richard A. Davis, Columbia University ; Muneya Matsui, Nanzan University ; Thomas Mikosch, University of Copenhagen ; Phyllis Wan, Columbia University
11:00 AM	Why Classical Measures of Dependence Do Not Satisfy Their Natural Axioms? — Gabor J Szekely, National Science Foundation
11:25 AM	Conditional Mean and Quantile Dependence Testing in High Dimension — Xianyang Zhang, Texas A&M University ; Shun Yao, University of Illinois at Urbana-Champaign ; Xiaofeng Shao, University of Illinois, At Urbana-Champaign
11:50 AM	A New Class of Measures for Testing Independence — Xiangrong Yin, University of Kentucky ; Qingcong Yuan, University of Kentucky
12:15 PM	Floor Discussion

637 * !	Thu, 8/3/2017, 10:30 AM - 12:20 PM	CC-303
Non-Standard Regression Models — Invited Papers
IMS , Section on Nonparametric Statistics
Organizer(s): Piet Groeneboom, Delft University of Technology
Chair(s): Piet Groeneboom, Delft University of Technology
10:35 AM	On Estimation of Regression Parameters with Current Status Data — Kim Hendrickx, Hasselt University ; Piet Groeneboom, Delft University of Technology
10:55 AM	Super-Efficiency with the Divide and Conquer Method — Moulinath Banerjee, University of Michigan ; Cecile Durot, University of Paris Ouest ; Bodhisattva Sen, Columbia University
11:15 AM	Least Squares Estimation in the Monotone Single Index Model — Fadoua Balabdaoui, Seminar fuer Statistik, ETH
11:35 AM	Spatial Adaptivity in Trend Filtering — Bodhisattva Sen, Columbia University
11:55 AM	Global error of smooth estimators for a monotone baseline hazard in the Cox model — Rik Lopuhaa, Delft University of Technology ; Eni Musta, Delft University of Technology
12:15 PM	Floor Discussion

639 * !	Thu, 8/3/2017, 10:30 AM - 12:20 PM	CC-314
Influential Observations: Detection and Modeling — Invited Papers
Section on Bayesian Statistical Science , International Society for Bayesian Analysis (ISBA) , IMS
Organizer(s): Mario Peruggia, The Ohio State University
Chair(s): Mario Peruggia, The Ohio State University
10:35 AM	Reconciling Curvature and Importance Sampling Based Procedures for Summarizing Case Influence in Bayesian Models — Zachary Micah Thomas, Eli Lilly and Company ; Mario Peruggia, The Ohio State University ; Steven MacEachern, The Ohio State University
11:00 AM	Residuals and Influence in Bayesian Ensemble Models — Robert McCulloch, Arizona State University ; Matthew Pratola, The Ohio State University
11:25 AM	Empirical Bayes Model Averaging with Influential Observations — Christopher Hans, The Ohio State University ; Mario Peruggia, The Ohio State University ; Junyan Wang, The Ohio State University
11:50 AM	Discussant: Dennis Cook, University of Minnesota
12:10 PM	Floor Discussion

641 * !	Thu, 8/3/2017, 10:30 AM - 12:20 PM	CC-309
Foundations of Network Analysis — Invited Papers
IMS , Royal Statistical Society , ENAR
Organizer(s): Walter Dempsey, University of Michigan
Chair(s): Chao Gao, University of Chicago
10:35 AM	Network Sparsity and Subsequent Inference — Joshua Cape, Johns Hopkins University ; Minh Tang, Johns Hopkins University ; Carey E Priebe, Johns Hopkins University
11:05 AM	Challenges in Network Sampling: Open Problems and Some Progress — Eric Kolaczyk, Boston University
11:35 AM	Accounting for the Sampling Scheme in Network Modeling — Harry Crane, Rutgers University ; Walter Dempsey, University of Michigan
12:05 PM	Floor Discussion

644 !	Thu, 8/3/2017, 10:30 AM - 12:20 PM	CC-318
Advancing Statistics in Universities: Deans' Viewpoints — Invited Panel
ASA Caucus of Academic Representatives , IMS
Organizer(s): Allan R Sampson, University of Pittsburgh
Chair(s): Allan R Sampson, University of Pittsburgh
10:35 AM	Advancing Statistics in Universities: Deans' Viewpoints
Panelists:	H. Joeseph Newton, Texas A&M Universtiy Montserrat Fuentes, Virginia Commonwealth University Rebecca Doerge, Carnegie-Mellon University Sally Morton, Virginia Tech Sastry Pantula, Oregon State University College of Science
12:10 PM	Floor Discussion

663	Thu, 8/3/2017, 10:30 AM - 12:20 PM	CC-304
New Developments in Modern Statistical Estimation Theory — Contributed Papers
IMS
Chair(s): Wenguang Sun, University of Southern California
10:35 AM	Estimation and Inference of Bounded Normal Mean — Yong Seok Park ; Jeremy M. G. Taylor, University of Michigan
10:50 AM	James-Stein Type Optimal Weight Choice for Frequentist Model Average Estimator — LIN YAO, SUNY Binghamton ; Ganggang Xu, Binghamton University ; Xingye Qiao, Binghamton University
11:05 AM	Multistage Estimation of a Negative Exponential Location with Applications in Health Studies — Sudeep R. Bapat, University of Connecticut ; Nitis Mukhopadhyay, University of Connecticut
11:20 AM	Endpoint Estimation for Observations with Normal Measurement Errors — Chen Zhou, De Nederlandsche Bank ; Liang Peng, Georgia State University ; Leng Xuan, Erasmus University Rotterdam ; Xing Wang, Georgia State University
11:35 AM	Efficient Asymptotic Variance Reduction When Estimating Volatility in High Frequency Data — Yoann Potiron, Keio University Faculty of Business and Commerce ; Simon Clinet, The University of Tokyo
11:50 AM	Adaptation in Log-Concave Density Estimation — Arlene Kyoung Hee Kim, Sungshin Women's University ; Adityanand Guntuboyina, UC Berkeley ; Richard J. Samworth, Statistical Laboratory, University of Cambridge
12:05 PM	Joint Asymptotics for Estimating the Fractal Indices of Bivariate Gaussian Processes — Yuzhen Zhou, University of Nebraska-Lincoln ; Yimin Xiao, Michigan State University

JSM 2017 Online Program

Activity Details

ASA Meetings Department

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