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