Name: 2019 Joint Statistical Meetings
Start: 2019-07-27T07:00:00+00:00
End: 2019-08-01
Location: Colorado Convention Center

Legend:
CC = Colorado Convention Center H = Hyatt Regency Denver at Colorado Convention Center
* = applied session ! = JSM meeting theme

Activity Details

CE_10C	Sun, 7/28/2019, 8:30 AM - 5:00 PM	CC-407
Teaching Data Science (ADDED FEE) — Professional Development Continuing Education Course
ASA, Section on Statistical Computing, Section on Statistics and Data Science Education
Instructor(s): Mine Cetinkaya-Rundel, Duke University
Success in data science and statistics is dependent on the development of both analytical and computational skills. As statistics educators we are more familiar and comfortable with teaching the former, but the latter is becoming increasingly important. The goal of this workshop is to equip educators with concrete information on content and infrastructure for painlessly introducing modern computation into a data science and/or statistics curriculum. In addition to gaining technical knowledge, participants will engage in discussion around the decisions that go into choosing infrastructure and developing curriculum. Workshop attendees will work through several exercises from existing courses and get first-hand experience with using relevant tool-chains and techniques, including R/RStudio, literate programming with R Markdown, and collaboration, version control, and automated feedback with Git/GitHub. We will also discuss best practices for configuring and deploying classroom infrastructures to support these tools. This workshop is aimed at participants who are interested in the role of computing in either a Statistics or Data Science curriculum, including faculty designing new courses/programs and those interested in adding or improving a computational component to an existing course. A basic knowledge of R is assumed and familiarity with Git is preferred.
8:30 AM	Teaching Data Science (ADDED FEE) Mine Cetinkaya-Rundel, Duke University

8 * !	Sun, 7/28/2019, 2:00 PM - 3:50 PM	CC-207
Machine Learning Methods and Applications: Making an Impact in Biomedical Research — Invited Papers
Section on Statistical Learning and Data Science, Biometrics Section, Section on Statistical Computing
Organizer(s): Juanjuan Fan, San Diego State University
Chair(s): Xiangrong Yin, University of Kentucky
2:05 PM	Finite Mixture Clustering of Risk Behaviors for an Infectious Disease Joseph Kang, Centers for Disease Control and Prevention (CDC)
2:30 PM	RELIEF-Based Feature Selection for Heterogeneous Treatment Effects with Massive Data Presentation Xiaogang Su, University of Texas, El Paso
2:55 PM	Matching Methods for Observational Data with Small Group Sizes and Mising Covariates Presentation Juanjuan Fan, San Diego State University; Afrooz Jahedi, San Diego State University; Tristan Hillis, San Diego State University; Ralph-Axel Mueller, San Diego State University
3:20 PM	Post-Market Surveillance of Arthroplasty Device Components Using Machine Learning Guy Cafri, Johnson & Johnson
3:45 PM	Floor Discussion

19 * !	Sun, 7/28/2019, 2:00 PM - 3:50 PM	CC-301
Statistical Computing and Statistical Graphics: Student Paper Award and Chambers Statistical Software Award — Topic Contributed Papers
Section on Statistical Computing, Section on Statistical Graphics
Organizer(s): Jun Yan, University of Connecticut
Chair(s): Jun Yan, University of Connecticut
2:05 PM	Vecchia-Laplace Approximations of Generalized Gaussian Processes for Big Non-Gaussian Spatial Data Presentation Daniel Zilber; Matthias Katzfuss, Texas A & M University
2:25 PM	Online Decentralized Leverage Score Sampling for Streaming Multidimensional Time Series Rui Xie, University of Georgia; Zengyan Wang, University of Georgia; Shuyang Bai, University of Georgia; Ping Ma, University of Georgia; Wenxuan Zhong, University of Georgia
2:45 PM	The R Conf Package for Plotting Likelihood-Ratio Based Confidence Regions for Two-Parameter Univariate Probability Models Presentation Christopher Weld, William & Mary; Andrew Loh, William & Mary; Lawrence Leemis, William & Mary
3:05 PM	Computing High-Dimensional Normal and Student-T Probabilities with Tile-Low-Rank Quasi-Monte Carlo and Block Reordering Presentation Jian Cao, King Abdullah University of Science and Technology; Marc Genton, King Abdullah University of Science and Technology; David Keyes, King Abdullah University of Science and Technology; George Turkiyyah, American University of Beirut
3:25 PM	A New Tidy Data Structure to Support Exploration and Modeling of Temporal Data Earo Wang, Monash University; Dianne Cook, Monash University; Rob J Hyndman, Monash Univeristy
3:45 PM	Floor Discussion

52 * !	Sun, 7/28/2019, 4:00 PM - 5:50 PM	CC-501
The 2018 Statistical Computing and Graphics Award — Invited Papers
Section on Statistical Computing, Section on Statistical Graphics
Organizer(s): Jun Yan, University of Connecticut
Chair(s): Michael Kane, Yale
4:05 PM	Some Thoughts on Languages for Statistical Computing and Graphics Presentation Luke Tierney, University of Iowa
4:30 PM	Visible and Invisible: Statistical Graphics and Computing Infrastructure Thomas Lumley, University of Auckland
4:55 PM	Lessons Learned in Interactive and Dynamic Graphics Heike Hofmann, Iowa State University
5:20 PM	The Estimable Luke Tierney -- and Estimability in R Presentation Russell V. Lenth, University of Iowa
5:45 PM	Floor Discussion

59 * !	Sun, 7/28/2019, 4:00 PM - 5:50 PM	CC-605
Deep Learning in Statistics: Really?! — Topic Contributed Papers
Section on Statistical Learning and Data Science, Section on Statistical Computing, Biometrics Section, Text Analysis Interest Group
Organizer(s): Wei Pan, University of Minnesota
Chair(s): Wei Pan, University of Minnesota
4:05 PM	Embedding Learning Presentation Ben Dai, University of Minnesota; Xiaotong Shen, University of Minnesota
4:25 PM	Deep Learning in Pathological Image Analysis Guanghua Xiao, UT Southwestern Medical Center; Shidan Wang, UT Southwestern Medical Center
4:45 PM	Complex Disease Risk Prediction via a Deep Learning Method Chong Wu, Florida State University
5:05 PM	Incorporating Biological Network to Build Deep Learning Models for Gene Expression Data Tianwei Yu, Emory University; Yunchuan Kong, Emory University
5:25 PM	Graph Convolutional Neural Networks for Multiple Gene Networks HU Yang, Central University of Finance and Economics; Wei Pan, University of Minnesota
5:45 PM	Floor Discussion

64 *	Sun, 7/28/2019, 4:00 PM - 5:50 PM	CC-705
Modeling Uncertainty in Energy Systems — Topic Contributed Papers
Section on Statistics and the Environment, Section on Statistical Computing
Organizer(s): Stefano Castruccio, University of Notre Dame
Chair(s): Stefano Castruccio, University of Notre Dame
4:05 PM	A High Resolution Ensemble to Quantify Wind Energy Resources in Saudi Arabia Paolo Giani, University of Notre Dame; Wanfang Chen, King Abdullah University of Science and Technology; Felipe Tagle, University of Notre Dame; Stefano Castruccio, University of Notre Dame; Marc Genton, King Abdullah University of Science and Technology; Paola Crippa, University of Notre Dame
4:25 PM	A Stochastic Generator of Global Wind Ensembles Jaehong Jeong, University of Maine
4:45 PM	Incorporating Photovoltaic and Load Uncertainty into Remote Microgrid Design Optimization Amanda S Hering, Baylor University; David Morton, Northwestern University; Alexander Zolan, University of Texas at Austin; Alexandra Newman, Colorado School of Mines
5:05 PM	Modeling and Prediction of Non-Stationary Gaussian Fields with Application to Wind Data in Saudi Arabia Presentation Amanda Lenzi, King Abdullah University of Science and Technology; Marc Genton, King Abdullah University of Science and Technology; Stefano Castruccio, University of Notre Dame; Håvard Rue, King Abdullah University of Science and Technology
5:25 PM	Assessing Wind Energy Resources in the New Mega-City NEOM Marc Genton, King Abdullah University of Science and Technology
5:45 PM	Floor Discussion

67 !	Sun, 7/28/2019, 4:00 PM - 5:50 PM	CC-203
Believable Big Bayes: Large-Scale Bayesian Inference with Finite-Data Guarantees — Topic Contributed Papers
SSC, International Society for Bayesian Analysis (ISBA), Section on Bayesian Statistical Science, Section on Statistical Computing
Organizer(s): Trevor Campbell, University of British Columbia
Chair(s): Tamara Broderick, Massachusetts Institute of Technology
4:05 PM	Variational Inference You Can Trust: a New Approach to Boosting Trevor Campbell, University of British Columbia
4:25 PM	A Scalable, Robust Bayesian Approach to Finding Mutational Signatures in Human Cancer Jonathan Huggins, Harvard School of Public Health
4:45 PM	Detecting Anomalous Structure in Multivariate Data Streams Alexander Fisch, Lancaster University; Idris Eckley, Lancaster University; Paul Fearnhead, Lancaster University
5:05 PM	Diffusion-Stein Sample Quality Measures for Distributions in Finite and Infinite Dimensions Andrew Duncan, Imperial College London
5:25 PM	Generalized Bilinear Models for Bias Correction in Large-Scale Genomics Data Jeffrey Miller, Harvard TH Chan School of Public Health
5:45 PM	Floor Discussion

86	Sun, 7/28/2019, 4:00 PM - 4:45 PM	CC-Hall C
SPEED: Data Challenge Part 2 — Contributed Poster Presentations
Government Statistics Section, Section for Statistical Programmers and Analysts, Section on Statistical Computing
Chair(s): Wendy L Martinez, Bureau of Labor Statistics
Oral Presentations for this session.
1:	Measuring Gentrification Over Time with the NYCHVS Robert Montgomery, NORC; Quentin Brummet, NORC; Nola du Toit, NORC at the University of Chicago; Peter Herman, NORC at the University of Chicago; Edward Mulrow, NORC at the University of Chicago
2:	Data Challenge Expo Darcy Hille, Merck & Company Inc; Ellen Snyder, Merck
3:	Interactive Visualization of Housing Condition Changes in NYC Qi Qi, University of Connecticut; Jun Yan, University of Connecticut
4:	Findings from Analysis and Visualization of the New York City Housing and Vacancy Survey Data Nels Grevstad, Metropolitan State University of Denver; Rachel Rosebrook, Metropolitan State University of Denver; Lance Barto, Metropolitan State University of Denver; Gil Leibovich, Metropolitan State University of Denver; Elizabeth Foster, Metropolitan State University of Denver; ThienNgo Le, Metropolitan State University of Denver; Kelsey Smith, Metropolitan State University of Denver; Nathanael Whitney, Metropolitan State University of Denver; Zoe Girkin, Metropolitan State University of Denver; Ahern Nelson, Metropolitan State University of Denver; Karan Bhargava, Metropolitan State University of Denver; Alex Whalen-Wagner, Metropolitan State University of Denver; Gemma Hoeppner, Metropolitan State University of Denver; Larry Breeden, Metropolitan State University of Denver; Ayako Zrust, Metropolitan State University of Denver; Travis Rebhan, Metropolitan State University of Denver; Anayeli Ochoa, Metropolitan State University of Denver
6:	Measuring Gentrification: a Data Driven Approach Steven Stier; Hend Aljobaily, University of Northern Colorado; Kofi Wagya, University of Northern Colorado; Michael Oduro-Safo, University of Northern Colorado
7:	Changes in Quality Housing Index in New York City Tuan Nguyen, University of Evansville; Mark Mozina, University of Evansville; Colton Albin, University of Evansville; Xianrui She, University of Evansville; Andrew Moore, University of Evansville
8:	Housing Affordability and Immigration: An Exploratory Analysis in New York City Jhonatan Medri, Utah State University; Braden Probst
9:	Statistical Analysis of the Association Between Housing Quality/Gentrification and Resident Behaviors in New York City Hon Keung Tony Ng, Southern Methodist University; Leqi Chen, Southern Methodist University; Jingzhou Liu, Southern Methodist University; Lynne Stokes, Southern Methodist University; Lang Xu, Southern Methodist University; Greg Guggenmos, Southern Methodist University; Madeline Hamilton, Southern Methodist University
10:	An Analysis of Housing Quality in New York City Jordan Rodu, University of Virginia
11:	Comparing NYCHVS Responses About Housing Issues to NYC 311 Complaint Records Letisha Smith
12:	Immigrant Residency and Happiness in New York City Alison Tuiyott, Miami University of Ohio; Thomas J Fisher, Miami University; Karsten Maurer, Miami University
13:	An Analysis of Rent-Control Policy on Housing Quality Benjamin Schweitzer, Miami University; Thomas J Fisher, Miami University; Karsten Maurer, Miami University
14:	An Analysis of Immigrants and House Condition in New York City Xiang Shen, George Washington University; Mingze Zhang, George Washington University; Shunyan Luo, George Washington University
15:	Correlates and Changes in New York City Housing Densities from 2002 to 2017 Elizabeth Pirraglia, NYU School of Medicine; Matthias Altwicker, NYIT; Andrea Troxel, NYU School of Medicine
Oral Presentations for this session.

120 * !	Mon, 7/29/2019, 8:30 AM - 10:20 AM	CC-712
Learn Something New: Techniques for Broadening Your Statistical Skillset — Topic Contributed Papers
Committee on Applied Statisticians, Section on Statistical Consulting, Section on Statistical Computing
Organizer(s): Lauren Hund, Sandia National Laboratories
Chair(s): Adah Zhang, Sandia National Laboratories
8:35 AM	Statistical Thinking and Analysis for Large and Complex Data Presentation Joanne Wendelberger, Los Alamos National Laboratory
8:55 AM	Sharpening the Tools in Your Data Science Toolbox Presentation Jessica Minnier, Oregon Health & Science University
9:15 AM	What's Your Point? Flipping the Paradigm for Communication in Statistical Science Elizabeth Mannshardt, US Environmental Protection Agency
9:35 AM	Lessons Learned from Collecting and Analyzing High-Dimensional GPS Data on Adolescent Activity Patterns Catherine A. Calder, The Ohio State University; Christopher R. Browning, The Ohio State University; Bethany Boettner, The Ohio State University; Kori Khan, The Ohio State University
9:55 AM	Discussant: Gabriel Huerta, University of New Mexico
10:15 AM	Floor Discussion

121 *	Mon, 7/29/2019, 8:30 AM - 10:20 AM	CC-708
Handling Large Dimensionality, Skewness and Non-Stationarity Through Multi-Resolution Spatial Modeling — Topic Contributed Papers
Section on Statistics and the Environment, Section on Bayesian Statistical Science, Section on Statistical Computing
Organizer(s): Veronica J. Berrocal, University of Michigan
Chair(s): Veronica J. Berrocal, University of Michigan
8:35 AM	Models for Large Multivariate Spatial Data Soutir Bandyopadhyay, Colorado School of Mines
8:55 AM	A Bi-Resolution Spatial Model Based on the Skew-T Distribution Stefano Castruccio, University of Notre Dame; Felipe Tagle, University of Notre Dame; Marc Genton, King Abdullah University of Science and Technology
9:15 AM	Using the MRA Approximation to Integrate Multiple Data Sources on Temperature Presentation Colin Lewis-Beck; Veronica J. Berrocal, University of Michigan; Joon Jin Song, Baylor University
9:35 AM	Multi-Scale Models for Large Non-Stationary Spatial Data Sets Bruno Sanso, University of California Santa Cruz; Daniel Kirsner, University of California Santa Cruz; Rajarshi Guhaniyogi, University of California, SC
9:55 AM	Conjugate Nearest Neighbor Gaussian Process Models for Efficient Statistical Interpolation of Large Spatial Data Andrew Finley, Michigan State University; Shinichiro Shirota, University of California, Los Angeles; Sudipto Banerjee, UCLA
10:15 AM	Floor Discussion

122 !	Mon, 7/29/2019, 8:30 AM - 10:20 AM	CC-603
Novel Statistical Methods in the Analysis of Big Data — Topic Contributed Papers
Section on Statistical Computing, International Chinese Statistical Association, Section on Statistical Learning and Data Science
Organizer(s): Elizabeth Schifano, University of Connecticut
Chair(s): Ming-Hui Chen, University of Connecticut
8:35 AM	Online Updating of Survival Analysis Elizabeth Schifano, University of Connecticut; Jing Wu, University of Rhode Island; Ming-Hui Chen, University of Connecticut; Jun Yan, University of Connecticut
8:55 AM	Optimal Subsampling: Sampling with Replacement Vs Poisson Sampling HaiYing Wang, University of Connecticut; Jiahui Zou, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
9:15 AM	Leverage Score Sampling for Multidimensional Streaming Time Series Shuyang Bai, University of Georgia; Rui Xie, University of Georgia; Ping Ma, University of Georgia; Wenxuan Zhong, University of Georgia; Zengyan Wang, University of Georgia
9:35 AM	Subsampled Information Criterion for Bayesian Model Selection in Big Data Setting Guanyu Hu, University of Connecticut; Lijiang Geng, University of Connecticut ; Yishu Xue, University of Connecticut
9:55 AM	Modified Multidimensional Scaling Qiang Sun, University of Toronto
10:15 AM	Floor Discussion

177	Mon, 7/29/2019, 10:30 AM - 12:20 PM	CC-710
Big Data and Computationally Intensive Methods — Contributed Papers
Section on Statistical Computing
Chair(s): Yafeng Zhang, Google
10:35 AM	Multiple Treatment Assessment via Propensity Scores in Heavy Censoring Multivariate Settings: Application to Organ Transplantation Jonathan Yu, Virginia Commonwealth University; Dipankar Bandyopadyay, Virginia Commonwealth University; Le Kang, Virginia Commonwealth University
10:50 AM	Hybrid Ridge-Lasso Regression Saeed Aldahmani, UAE University; Taoufik Zoubeidi, UAE University
11:05 AM	A Data-Driven Multiple Testing Procedure Nasrine Bendjilali, Rowan University; Boualem Bendjilali, RVCC; Wei-Min Huang, Lehigh University
11:20 AM	Damped Anderson Acceleration with Restarts and Monotonicity Control for Accelerating EM and EM-Like Algorithms Presentation Nicholas Henderson, Johns Hopkins University; Ravi Varadhan, Johns Hopkins University
11:35 AM	Comparison of Bootstrapping Techniques in Multivariate Time Series Presentation Daniel Cirkovic, University of Miami-Oxford; Jing Zhang, Miami University; Thomas J Fisher, Miami University
11:50 AM	Sampling Distribution of Pattern Statistics in Sparse Markov Models Presentation Donald Martin, NC State University
12:05 PM	A Sequential Boothstrap/Resampling Method Presentation Silvia Sharna, Ball State University; Mian Adnan, Indiana University

218874	Mon, 7/29/2019, 12:30 PM - 2:00 PM	H-Mineral Hall E
Sections on Statistical Computing and Statistical Graphics Executive Council Meeting — Other Cmte/Business
Section on Statistical Computing, Section on Statistical Graphics
Chair(s): Dianne Cook, Monash University; Wendy L Martinez, Bureau of Labor Statistics

211 * !	Mon, 7/29/2019, 2:00 PM - 3:50 PM	CC-605
Getting to the Slope of Enlightenment with EHR Data — Invited Papers
Section on Statistical Computing, Section on Statistical Learning and Data Science, Biometrics Section
Organizer(s): Jeffrey Leek, Johns Hopkins Bloomberg School of Public Health
Chair(s): Jeffrey Leek, Johns Hopkins Bloomberg School of Public Health
2:05 PM	Handling Sampling and Selection Bias in Phenome-Wide Association Studies Presentation Bhramar Mukherjee, University of Michigan
2:30 PM	Complex Data in, Nuanced Answers Out: Lessons Learned Analyzing Electronic Health Record Data in Oncology Sandra Griffith, Flatiron Health
2:55 PM	Challenges in Augmenting Randomized Trials with Observational Health Records Presentation Lucy D'Agostino McGowan, Johns Hopkins Bloomberg School of Public Health
3:20 PM	Discussant: Sherri Rose, Harvard Medical School
3:45 PM	Floor Discussion

217 !	Mon, 7/29/2019, 2:00 PM - 3:50 PM	CC-301
Computing Making Impact: The Best of JCGS — Invited Papers
JCGS-Journal of Computational and Graphical Statistics, Section on Statistical Computing, Section on Statistical Graphics
Organizer(s): Dianne Cook, Monash University
Chair(s): Tyler McCormick, University of Washington
2:05 PM	Data Science: a Three Ring Circus or a Big Tent? Presentation Jennifer Bryan, RStudio, University of British Columbia; Hadley Wickham, RStudio
2:25 PM	Identifying Mixtures of Mixtures Using Bayesian Estimation Bettina Grün, Johannes Kepler Universität; Gertraud Malsiner-Walli, Wirtschaftsuniversität Wien; Sylvia Frühwirth-Schnatter, Wirtschaftsuniversität Wien
2:45 PM	Bayesian Fused Lasso Regression for Dynamic Binary Networks Presentation Brenda Betancourt, University of Florida
3:05 PM	Designing Modular Software: a Case Study in Introductory Statistics Andrea Kaplan, Duke University; Eric Hare, Omni Analytics
3:25 PM	Discussant: Dianne Cook, Monash University
3:45 PM	Floor Discussion

228 * !	Mon, 7/29/2019, 2:00 PM - 3:50 PM	CC-607
Interpreting Machine Learning Models: Opportunities, Challenges, and Applications — Topic Contributed Papers
Section on Statistical Learning and Data Science, Section on Nonparametric Statistics, Section on Statistical Computing
Organizer(s): Vijayan Nair, Wells Fargo & University of Michigan, Ann Arbor
Chair(s): Joel B. Brodsky, Wells Fargo
2:05 PM	Understanding the Effects of Predictor Variables in Black-Box Supervised Learning Models Presentation Daniel W Apley, Northwestern University
2:25 PM	Deep Insights into Explainability and Interpretability of Machine Learning Algorithms and Applications to Risk Management Presentation Jie Chen, Wells Fargo
2:45 PM	Increasing Trust and Interpretability in Machine Learning with Model Debugging Presentation Patrick Hall, H2O.ai
3:05 PM	Detecting Interpretable Insights from Large-Scale Time Series Data Qing Feng, Facebook; Sean Taylor , Facebook
3:25 PM	Floor Discussion

255	Mon, 7/29/2019, 2:00 PM - 3:50 PM	CC-Hall C
Contributed Poster Presentations: Section on Statistical Computing — Contributed Poster Presentations
Section on Statistical Computing
Chair(s): Wendy Meiring, University of California At Santa Barbara
42:	Accounting for the Uncertainty of Nuisance Parameter in Power and Sample Size Calculation Chuchu Cheng, Boston College; Hao Wu, Vanderbilt University
43:	Computational Effort of Multiple Hypothesis Testing Georg Hahn
44:	Stochastic Gradient MCMC for State Space Models Christopher Aicher, University of Washington
45:	Computational Aspects of Model-Based Quantile Regression with Discrete Responses Xuan Shi, University of Kentucky; Derek Young, University of Kentucky; Carlos Lamarche, University of Kentucky
46:	Fitting Flexible Models for Count Data: COM-Poisson Regression, Bivariate, Multinomial and Mixed Models Darcy Steeg Morris, U.S. Census Bureau; Kimberly F Sellers, Georgetown University
47:	CPS Analysis: Self-Contained Validation of Biological Clustering Results Lixiang Zhang, PSU; Jia Li, Penn State University; Lin Lin, PSU
50:	Bootstrapping Transfer Function Models Maher Qumsiyeh; Didiere Hirwantwari, University of Dayton
51:	Multi-Level Monte Carlo Using Quasi-Random Numbers Lu Vy, University of Colorado Denver; Erin Austin, University of Colorado Denver; Yaning Liu, University of Colorado Denver
52:	Asymptotic Analysis of Wilf Partitions Using Generating Functions Kevin LaMaster; Mark Ward, Purdue University
53:	Optimal Two-Stage Adaptive Subsampling Design for Softmax Regression Yaqiong Yao, University of Connecticut; HaiYing Wang, University of Connecticut; Jiahui Zou, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
54:	The Decomposition of Quadratic Forms Under Matrix Variate Skew Normal Distribution Ziwei Ma, New Mexico State University; Tonghui Wang, New Mexico State University
55:	Score Approximations for the Evolutionary Spectrum Model for Large Spatial Data Amanda Muyskens, North Carolina State University; Joseph Guinness, Cornell University
56:	Edge Deletion Tests in Graphical Models for Multivariate Time Series Marco Reale, University of Canterbury; Chris Price, University of Canterbury; Anna Lin, Statistics New Zealand; Rory Ellis, University of Canterbury
57:	Double Matched Matrix Factorization Dongbang Yuan, Texas A&M University; Irina Gaynanova, Texas A&M Univeristy
59:	Nested Logistic Regression Model for Multiclass Rare Event Data Using Classification Cost Masaaki Okabe, Doshisha University; Hiroshi Yadohisa, Doshisha University
60:	Autocorrelation Function Estimation Using Penalized Least Squares Xiyan Tan, Clemson University; Colin Mark Gallagher, Clemson University
61:	Generalised Boosted Forests; Variance Estimation and Inference Indrayudh Ghosal, Cornell University
62:	Mediation Analysis with Binary Mediators: a New Parametric Method and R Programs Yujiao Mai, St. Jude Children's Research Hospital; Deo Kumar Srivastava, St. Jude Children's Research Hospital; Hui Zhang, St. Jude Children's Research Hospital
63:	Applying an Intrinsic Conditional Autoregressive Reference Prior for Areal Data Erica Porter, Virginia Tech; Matthew Keefe, The Walt Disney Company; Christopher Franck, Virginia Tech; Marco Ferreira, Virginia Tech
64:	Data Monitoring and Quality Control for Disease Growth in Longitudinal Medical Imaging Data Kari Sorge, UCLA; Grace Kim, UCLA; Jihey Lee, UCLA

218875	Mon, 7/29/2019, 6:30 PM - 8:00 PM	H-Centennial Ballroom B
Sections on Statistical Computing and Statistics Graphics Mixer — Other Cmte/Business
Section on Statistical Computing, Section on Statistical Graphics
Chair(s): Dianne Cook, Monash University; Wendy L Martinez, Bureau of Labor Statistics

278 * !	Tue, 7/30/2019, 8:30 AM - 10:20 AM	CC-504
Emerging Ideas in Predictive Inference — Invited Papers
Section on Statistical Learning and Data Science, Section on Nonparametric Statistics, Section on Statistical Computing
Organizer(s): Lucas Mentch, University of Pittsburgh
Chair(s): Yifan Cui, University of Pennsylvania
8:35 AM	Predictive Inference with Random Forests Lucas Mentch, University of Pittsburgh
9:00 AM	Forward Stability and Model Path Selection Nicholas Kissel, University of Pittsburgh; Lucas Mentch, University of Pittsburgh
9:25 AM	Relaxing the Assumptions of Model-X Knockoffs Lucas Janson, Harvard University; Dongming Huang, Harvard University
9:50 AM	Recent Advances in Conformal Prediction Presentation Larry Wasserman, Carnegie Mellon University
10:15 AM	Floor Discussion

287 * !	Tue, 7/30/2019, 8:30 AM - 10:20 AM	CC-113
Advanced Stochastic Models and Inference Methods for Large-Scale Phylogenetics — Topic Contributed Papers
Section on Statistics in Genomics and Genetics, Section on Statistical Computing, Section on Statistics in Epidemiology
Organizer(s): Guy Baele, Rega Institute / KU Leuven
Chair(s): Mandev Gill, Rega Institute, KU Leuven
8:35 AM	Fast and Robust Evolutionary Rate and Selection Pressure Inference Using Variational Bayes Techniques Presentation Sergei Pond, Temple University
8:55 AM	Modeling Site-To-Site Variability of Synonymous Substitution Rates: Impacts on Statistical Inference Spencer Muse, North Carolina State University; Sadie Wisotsky, Temple University; Sergei Kosakovsky Pond, Temple University
9:15 AM	Fitness-Dependent Birth-Death Models for Phylodynamic Inference of Adaptive Evolution Presentation David Rasmussen, North Carolina State University; Tanja Stadler, ETH Zurich
9:35 AM	Towards Realtime Bayesian Inference for Pathogen Phylodynamics Presentation Guy Baele, Rega Institute / KU Leuven; Mandev Gill, Rega Institute, KU Leuven; Philippe Lemey, Rega Institute, KU Leuven; Marc Suchard, UCLA; Andrew Rambaut, University of Edinburgh
9:55 AM	Floor Discussion

290 * !	Tue, 7/30/2019, 8:30 AM - 10:20 AM	CC-703
Big Data in Time Series and Spatial Data Analysis: Theory and Applications — Topic Contributed Papers
Royal Statistical Society, IMS, Section on Statistical Computing
Organizer(s): Sucharita Ghosh, Swiss Federal Research Institute WSL
Chair(s): Sucharita Ghosh, Swiss Federal Research Institute WSL
8:35 AM	Two Sample Testing for Multivariate Functional Data Presentation Klaus Telkmann, University of California Irvine; Dustin Pluta, University of California Irvine; Hernando Ombao, King Abdullah University of Science and Technology (KAUST); Babak Shahbaba, University of California Irvine
8:55 AM	Parameter Estimation for Big Data in Time Series and Random Fields Presentation Adam Sykulski, Lancaster University; Sofia C Olhede, University College London; Arthur Guillaumin, University College London
9:15 AM	Nonparametric Regression Under Semi-Long Range Dependence Farzad Sabzikar, Iowa State University
9:35 AM	Further Development of the Double Conditional Smoothing for Nonparametric Surfaces Under a Lattice Spatial Model Presentation Yuanhua Feng; Bastian Schäfer, Paderborn University
9:55 AM	Discussant: Jan Beran, University of Konstanz
10:15 AM	Floor Discussion

305 !	Tue, 7/30/2019, 8:30 AM - 10:20 AM	CC-301
Bayesian Modeling and Variable Selection Methods — Contributed Papers
Section on Statistical Computing, International Society for Bayesian Analysis (ISBA), Section on Bayesian Statistical Science
Chair(s): Augustus Jayaraj, Cornell University
8:35 AM	A New Generalized Inverse Gaussian Distribution with Bayesian Estimators Presentation Kenneth R Goward, Central Michigan University; Chin-I Cheng, Central Michigan University; Kahadawala Cooray, Central Michigan University
8:50 AM	Estimating Random Walk Centrality Nirodha Mihirani Epasinghege Dona, University of Manitoba; Brad Johnson, University of Manitoba
9:05 AM	Variable Selection Techniques for Model-Based Clustering of Directional Data Presentation Semhar Michael, South Dakota State University; Damon Bayer, South Dakota State Univesity
9:20 AM	Implicit Regularization via Hadamard Product Parametrization in Linear Regression Peng Zhao, Florida State University; Yun Yang, University of Illinois Urbana-Champaign; Qiao-chu He, Southern University of Science and Technology
9:35 AM	High-Dimensional Controlled Variable Selection for Ordinal Outcomes Presentation Han Fu, The Ohio State University; Kellie Archer, Ohio State University
9:50 AM	Variable Selection for High-Dimensional Nodal Attributes in Social Networks Presentation Jia Wang, Penn State University; Runze Li, Penn State University
10:05 AM	Incomplete High-Dimensional Inverse Covariance Estimation Yunxi Zhang, University of Mississippi Medical Center; Soeun Kim, University of Texas Health Science Center at Houston

316 * !	Tue, 7/30/2019, 10:30 AM - 12:20 PM	CC-702
Emerging Advances of Innovative Computational Skills with Unconventional Likelihoods — Invited Papers
Section on Statistical Computing
Organizer(s): Jiwei Zhao, State University of New York At Buffalo
Chair(s): Jiwei Zhao, State University of New York At Buffalo
10:35 AM	A Broad Framework for Likelihood Alternatives in View of Small, Very Large, and Variable-Size Data Presentation Geert Molenberghs, Universiteit Hasselt & Katholieke Universiteit Leuven
11:00 AM	Maximum Empirical Likelihood Estimation and Related Topics Anton Schick, Binghamton University
11:25 AM	A Likelihood Ratio Test for Shape-Constraint Density Kwun Chuen Gary Chan, University of Washington
11:50 AM	Community Detection with Dependent Connectivity Yubai Yuan, University of Illinois at Urbana-Champaign; Annie Qu, University of Illinois at Urbana-Champaign
12:15 PM	Floor Discussion

386 * !	Tue, 7/30/2019, 2:00 PM - 3:50 PM	CC-201
Filtering Methods for Spatio-Temporal Big Data Applications — Invited Papers
Section on Statistics and the Environment, Section on Physical and Engineering Sciences, Section on Statistical Computing
Organizer(s): Matthias Katzfuss, Texas A & M University
Chair(s): Christopher K. Wikle, University of Missouri
2:05 PM	Ensemble Kalman Methods for High-Dimensional Hierarchical Dynamic Space-Time Models Matthias Katzfuss, Texas A & M University; Christopher K. Wikle, University of Missouri; Jonathan R Stroud, Georgetown University
2:30 PM	Nonlinear, Non-Gaussian Extensions for Serial Ensemble Filter Data Assimilation Presentation Jeffrey Anderson, National Center for Atmospheric Research
2:55 PM	Improving Particle Filter Performance in Spatially-Extended Problems by Smoothing Observations Presentation Ian Grooms, University of Colorado Boulder; Gregor Robinson, University of Colorado Boulder; William Kleiber, University of Colorado
3:20 PM	Particle Filters in High Dimensions Presentation Peter Jan van Leeuwen, Colorado State University and University of Reading (UK); Manuel Pulido, University of Reading
3:45 PM	Floor Discussion

388 * !	Tue, 7/30/2019, 2:00 PM - 3:50 PM	CC-603
Building Bridges for Data Science Education — Invited Panel
Section on Statistics and Data Science Education, Section on Statistical Computing, Section on Statistical Learning and Data Science
Organizer(s): Mine Cetinkaya-Rundel, Duke University
Chair(s): Beth Chance, Cal Poly - San Luis Obispo
2:05 PM	Building Bridges for Data Science Education Presentation
Panelists:	Mine Cetinkaya-Rundel, Duke University Michael Posner, Villanova University Jeff Forbes, Duke University Andrea Danyluk, Williams College
3:45 PM	Floor Discussion

401 * !	Tue, 7/30/2019, 2:00 PM - 3:50 PM	CC-704
Why JavaScript? — Topic Contributed Panel
Section on Statistical Graphics, Section on Statistical Computing
Organizer(s): Joyce Robbins, Columbia University
Chair(s): Tim Hesterberg, Google
2:05 PM	Why JavaScript? Presentation 1 Presentation 2 Presentation 3
Panelists:	Karl Broman, University of Wisconsin Carson Sievert, RStudio Ramnath Vaidyanathan, DataCamp Joy Yang, Google
3:40 PM	Floor Discussion

412	Tue, 7/30/2019, 2:00 PM - 3:50 PM	CC-708
Data Science and Machine Learning Topics — Contributed Papers
Section on Statistical Computing
Chair(s): Qiao Ma, NORC at University of Chicago
2:05 PM	Modifications of the Syrjala Test for Testing Spatial Distribution Differences Between Two Populations Presentation Eric McKinney, Utah State University; Juergen Symanzik, Utah State University
2:20 PM	Positive Orthant Dirichlet Hyperspheric Distribution Presentation Jose Guardiola, Texas A&M University Corpus Christi; Eduardo Garcia Portugues, Universidad Carlos III de Madrid
2:35 PM	Identifying Influential Posters on Reddit Through Network Analysis Jonathan Lane, Activision Publishing; Aaron Sachs, Harvard University
2:50 PM	A Change-Point Detection and Clustering Method in the Recurrent-Event Context Presentation Qing Li, Iowa State University
3:05 PM	Estimating Multiple Precision Matrices Using Cluster Fusion Regularization Presentation Brad Price, West Virginia University; Aaron Molstad, Fred Hutchinson Cancer Research Center; Ben Sherwood, University of Kansas
3:20 PM	Gradient-Based Sparse Principal Component Analysis with Extensions to Online Learning Yixuan Qiu, Carnegie Mellon University; Jing Lei, Carnegie Mellon University; Kathryn Roeder, Carnegie Mellon University
3:35 PM	A General Multivariate Linear Mixed Model for Detecting Gene by Environment Interactions Presentation Hyeonju Kim, University of Tennessee Health Sci Ctr; Saunak Sen, University of Tennessee Health Sci Ctr

444 !	Wed, 7/31/2019, 8:30 AM - 10:20 AM	CC-505
Modern and Practical Solutions to Difficult High-Dimensional Regression Problems — Invited Papers
Section on Statistical Computing, International Association for Statistical Computing, Section on Statistical Learning and Data Science
Organizer(s): Maryclare Griffin, Cornell University Center for Applied Mathematics
Chair(s): Andee Kaplan, Duke University
8:35 AM	Informative Priors for Clustering Amy H Herring, Duke University; Sally Paganin, University of Padova; Andrew Olshan, UNC-Chapel Hill
8:55 AM	Bayesian Function-On-Scalars Regression for High-Dimensional Data Daniel R Kowal, Rice University; Daniel Bourgeois, Rice University
9:15 AM	Computationally-Efficient High-Dimensional Interaction Modeling Guo Yu, University of Washington; Ryan Tibshirani, Carnegie Mellon University; Jacob Bien, University of Southern California
9:35 AM	Data-Adaptive Additive Modeling Presentation Ashley Petersen, University of Minnesota; Daniela Witten, University of Washington
9:55 AM	Discussant: Tian Zheng, Columbia University
10:15 AM	Floor Discussion

452 * !	Wed, 7/31/2019, 8:30 AM - 10:20 AM	CC-710
Geometric Statistical and Computational Methods in Imaging — Topic Contributed Papers
Section on Statistics in Imaging, International Indian Statistical Association, Section on Statistical Computing
Organizer(s): Sebastian Kurtek, The Ohio State University
Chair(s): Sebastian Kurtek, The Ohio State University
8:35 AM	Density Estimation Under Multimodal Shape Constraints Anuj Srivastava, Florida State University
8:55 AM	Catalyst Acceleration for Non-Convex Optimization on Manifolds Presentation Lizhen Lin, University of Notre Dame; Bayan Saparbayeva, University of Notre Dame; Michael Minyi Zhang, Princeton University; David Dunson, Duke University
9:15 AM	Geometric Aspects of Warped Functional Data, and Local Regression Presentation Karthik Bharath, University of Nottingham
9:35 AM	Signal Subgraph Learning for Longitudinal Structural Brain Networks Presentation Lu Wang, Central South University
9:55 AM	Object Data Driven Discovery Presentation 1 Presentation 2 Ian L Dryden, University of Nottingham
10:15 AM	Floor Discussion

465	Wed, 7/31/2019, 8:30 AM - 10:20 AM	CC-501
SPEED: Statistical Computing: Methods, Implementation, and Application, Part 1 — Contributed Speed
Section on Statistical Computing
Chair(s): Michael Weylandt, Rice University
Poster Presentations for this session.
8:35 AM	Sure Independence Screening (SIS) for Multiple Functional Regression Model Presentation Yuan Yuan, Auburn University; Nedret Billor, Auburn University
8:40 AM	Creation of Two R Shiny Applications to Illustrate and Accompany the growClusters Package Presentation Randall Powers, U.S. Bureau of Labor Statistics; Terrance Savitsky, Bureau of Labor Statistics; Wendy L Martinez, Bureau of Labor Statistics
8:45 AM	Generalized Causal Mediation and Path Analysis and Its R Package “gmediation” Presentation Jang Ik Cho, Eli Lilly and Company; Jeffrey M Albert, Case Western Reserve University
8:50 AM	Spatial DNA: Measuring Similarity of Geolocation Data Sets with Applications to Forensics Presentation Christopher Galbraith, University of California, Irvine; Padhraic Smyth, University of California, Irvine
8:55 AM	Sampling Using Langevin Diffusion Presentation Riddhiman Bhattacharya, University of Minnesota
9:00 AM	Rapid Numerical Approximation of Spatial Covariance Functions Over Irregular Data Regions Presentation 1 Presentation 2 Presentation 3 Peter Simonson, Colorado School of Mines; Doug Nychka, Colorado School of Mines; Soutir Bandyopadhyay, Colorado School of Mines
9:05 AM	Predicting Lattice Reduction on Ideal Lattices (PeRIL) Presentation 1 Presentation 2 Bryan Ek, Space and Naval Warfare Systems Center Atlantic; Bryan Williams, Space and Naval Warfare Systems Center Atlantic; Emily Nystrom, Naval Information Warfare Center Atlantic; Jamie Lyle, Space and Naval Warfare Systems Center Atlantic; Peter Curry, Space and Naval Warfare Systems Center Atlantic; Scott Batson, Space and Naval Warfare Systems Center Atlantic
9:10 AM	Exact Inference for Analyzing Contingency Tables in Finite Populations Presentation 1 Presentation 2 Shiva Dibaj, UT MD Anderson Cancer Center; Gregory Wilding, SUNY at Buffalo; Graham Warren, University of Kentucky
9:15 AM	A Simple Recipe for Making Accurate Parametric Inference in Finite Sample Presentation Mucyo Karemera, Penn State University; Stephane Guerrier, University of Geneva; Samuel Orso, University of Geneva; Maria-Pia Victoria-Feser, University of Geneva
9:20 AM	The Variance of the Interaction Term as Goal for Estimation Presentation 1 Presentation 2 Iman Jaljuli, Tel-Aviv University; Yoav Benjamini, Tel Aviv University
9:30 AM	A New Approach in Distribution Fitting for Grouped Data and Its Application in Measuring Income Distribution Ying-Ju Chen, University of Dayton; Tatjana Miljkovic, Miami University
9:35 AM	Spatial Location-Based Trajectory Modeling: Predicting the Success of an Crowdfunding Campaign Han Yu, University of Northern Colorado
9:40 AM	Embarrassingly Parallel Inference for Gaussian Processes Michael Minyi Zhang, Princeton University; Sinead Williamson, UT Austin
9:45 AM	Tidi_MIBI: a Tidy Pipeline for Microbiome Analysis and Visualization in R Presentation 1 Presentation 2 Charlie Carpenter, University of Colorado-Biostatistics
9:50 AM	Tensor Variate Models Applied to Sensor Data Peter Tait, McMaster University; Paul D McNicholas, McMaster University
9:55 AM	Using Information Criteria to Select Among Polynomial and “truly” Nonlinear Multilevel Models Presentation Wendy Christensen, University of California, Los Angeles; Jennifer Krull, University of California, Los Angeles
10:00 AM	Clustering Smoothed Dissimilarities in Tertiary Data: a Shrinkage-Based Approach Presentation 1 Presentation 2 Bridget Manning, University of South Carolina; David Hitchcock, University of South Carolina
10:05 AM	Incorporating Spatial Statistics into Routine Analysis of Agricultural Field Trials Presentation Julia Piaskowski, University of Idaho; Chad Jackson, University of Idaho; Juliet Marshall, University of Idaho; William J Price, University of Idaho
10:10 AM	Bootstrap in the Linear Model: a Comprehensive R Package Presentation Megan Heyman, Rose-Hulman Institute of Technology
10:15 AM	Floor Discussion

480 * !	Wed, 7/31/2019, 10:30 AM - 12:20 PM	CC-203
Novel Statistical Methods for Bioinformatics and Computational Biology — Invited Papers
Section on Statistics in Genomics and Genetics, Section on Statistical Computing, WNAR
Organizer(s): Ping Ma, University of Georgia
Chair(s): Ping Ma, University of Georgia
10:35 AM	Statistical Methods for Single Cell Regulomics Sunduz Keles, UW Madison; Daniel Conn, University of Wisconsin
11:00 AM	Bayesian Detection of Convergent Rate Changes of Conserved Noncoding Elements on Phylogenetic Trees Presentation Scott V Edwards, Harvard University; Jun S. Liu, Harvard University; Zhirui Hu, Harvard University; Timothy B Sackton, Harvard University
11:25 AM	Reference-Free Learning with Multiple Metagenomic Samples Presentation Wenxuan Zhong, University of Georgia
11:50 AM	B-Scaling: A Novel Nonparametric Data Fusion Method Yiwen Liu, University of Arizona; Xiaoxiao Sun, University of Arizona; Wenxuan Zhong, University of Georgia; Bing Li, The Pennsylvania State University
12:15 PM	Floor Discussion

495 * !	Wed, 7/31/2019, 10:30 AM - 12:20 PM	CC-502
Changepoints: Making an Impact — Topic Contributed Papers
Royal Statistical Society, Section on Statistical Computing, Business and Economic Statistics Section
Organizer(s): Rebecca Killick, Lancaster University, UK
Chair(s): David Matteson, Cornell University
10:35 AM	Distinguishing Short and Long-Memory When Testing for Changepoints in Climate Time-Series: Application to Surface Temperature Records Claudie Beaulieu, University of California, Santa Cruz; Rebecca Killick, Lancaster University, UK
10:55 AM	Detection and Estimation of Local Signals David Siegmund; Xiao Fang, Chinese University of Hong Kong
11:15 AM	Detecting Changes in Mean in the Presence of Autocovariance Presentation Euan McGonigle, Lancaster University; Rebecca Killick, Lancaster University, UK; Matthew Nunes, University of Bath
11:35 AM	Changepoint Analysis of Historical Battle Deaths Presentation Marina Knight, University of York; Brennen Fagan, University of York; Niall MacKay, University of York; Jamie Wood, University of York
11:55 AM	Influence Measures for Changepoint Segmentations Presentation Ines Wilms, Maastricht University; Rebecca Killick, Lancaster University, UK; David Matteson, Cornell University
12:15 PM	Floor Discussion

513	Wed, 7/31/2019, 10:30 AM - 12:20 PM	CC-706
Topics in Monte Carlo Simulation — Contributed Papers
Section on Statistical Computing
Chair(s): Sam Tyner, Iowa State University
10:35 AM	Real-Time Change Point Detection Presentation Kyungduk Ko, Boise State University
10:50 AM	Fast Spatial Inference in the Homogeneous Ising Model Presentation Ranjan Maitra, Iowa State University; Alejandro Murua, University of Montreal
11:05 AM	Fast Markov Chain Monte Carlo for High-Dimensional Bayesian Regression Models with Shrinkage Priors Presentation Rui Jin, University of Iowa; Aixin Tan, University of Iowa
11:20 AM	Efficient Sampling for Imbalanced Large Categorical Data Using Piece-Wise Deterministic Markov Chain Monte Carlo Presentation Deborshee Sen, Duke University; Matthias Sachs, Duke University ; David Dunson, Duke University; Jianfeng Lu, Duke University
11:35 AM	Stacking for Multimodal Posterior Distributions Yuling Yao, Columbia University; Andrew Gelman, Columbia University
11:50 AM	A Second-Order Adaptive Sampling Framework for Stochastic Gradient Descent David Newton, Purdue University; Raghu Pasupathy, Purdue University
12:15 PM	VIVID - Visualisation of Variable Importance Differences for Improved Understanding of Parkinson's Disease Samuel Mueller, The University of Sydney; Connor Smith, University of Sydney; Boris Guennewig, University of Sydney

531	Wed, 7/31/2019, 11:35 AM - 12:20 PM	CC-Hall C
SPEED: Statistical Computing: Methods, Implementation, and Application, Part 2 — Contributed Poster Presentations
Section on Statistical Computing, Section for Statistical Programmers and Analysts
Chair(s): Michael Weylandt, Rice University
Oral Presentations for this session.
1:	Sure Independence Screening (SIS) for Multiple Functional Regression Model Yuan Yuan, Auburn University; Nedret Billor, Auburn University
2:	Creation of Two R Shiny Applications to Illustrate and Accompany the growClusters Package Randall Powers, U.S. Bureau of Labor Statistics; Terrance Savitsky, Bureau of Labor Statistics; Wendy L Martinez, Bureau of Labor Statistics
3:	Generalized Causal Mediation and Path Analysis and Its R Package “gmediation” Jang Ik Cho, Eli Lilly and Company; Jeffrey M Albert, Case Western Reserve University
4:	Spatial DNA: Measuring Similarity of Geolocation Data Sets with Applications to Forensics Christopher Galbraith, University of California, Irvine; Padhraic Smyth, University of California, Irvine
5:	Sampling Using Langevin Diffusion Riddhiman Bhattacharya, University of Minnesota
6:	Rapid Numerical Approximation of Spatial Covariance Functions Over Irregular Data Regions Peter Simonson, Colorado School of Mines; Doug Nychka, Colorado School of Mines; Soutir Bandyopadhyay, Colorado School of Mines
7:	Predicting Lattice Reduction on Ideal Lattices (PeRIL) Bryan Ek, Space and Naval Warfare Systems Center Atlantic; Bryan Williams, Space and Naval Warfare Systems Center Atlantic; Emily Nystrom, Naval Information Warfare Center Atlantic; Jamie Lyle, Space and Naval Warfare Systems Center Atlantic; Peter Curry, Space and Naval Warfare Systems Center Atlantic; Scott Batson, Space and Naval Warfare Systems Center Atlantic
8:	Exact Inference for Analyzing Contingency Tables in Finite Populations Shiva Dibaj, UT MD Anderson Cancer Center; Gregory Wilding, SUNY at Buffalo; Graham Warren, University of Kentucky
9:	A Simple Recipe for Making Accurate Parametric Inference in Finite Sample Mucyo Karemera, Penn State University; Stephane Guerrier, University of Geneva; Samuel Orso, University of Geneva; Maria-Pia Victoria-Feser, University of Geneva
10:	The Variance of the Interaction Term as Goal for Estimation Iman Jaljuli, Tel-Aviv University; Yoav Benjamini, Tel Aviv University
11:	A New Approach in Distribution Fitting for Grouped Data and Its Application in Measuring Income Distribution Ying-Ju Chen, University of Dayton; Tatjana Miljkovic, Miami University
12:	Spatial Location-Based Trajectory Modeling: Predicting the Success of an Crowdfunding Campaign Han Yu, University of Northern Colorado
13:	Embarrassingly Parallel Inference for Gaussian Processes Michael Minyi Zhang, Princeton University; Sinead Williamson, UT Austin
15:	Tensor Variate Models Applied to Sensor Data Peter Tait, McMaster University; Paul D McNicholas, McMaster University
16:	Using Information Criteria to Select Among Polynomial and “truly” Nonlinear Multilevel Models Wendy Christensen, University of California, Los Angeles; Jennifer Krull, University of California, Los Angeles
17:	Clustering Smoothed Dissimilarities in Tertiary Data: a Shrinkage-Based Approach Bridget Manning, University of South Carolina; David Hitchcock, University of South Carolina
18:	Incorporating Spatial Statistics into Routine Analysis of Agricultural Field Trials Julia Piaskowski, University of Idaho; Chad Jackson, University of Idaho; Juliet Marshall, University of Idaho; William J Price, University of Idaho
19:	Bootstrap in the Linear Model: a Comprehensive R Package Megan Heyman, Rose-Hulman Institute of Technology
20:	Tidi_MIBI: a Tidy Pipeline for Microbiome Analysis and Visualization in R Charlie Carpenter, University of Colorado-Biostatistics
Oral Presentations for this session.

537	Wed, 7/31/2019, 12:30 PM - 1:50 PM	H-Centennial Ballroom G-H
Section on Statistical Computing P.M. Roundtable Discussion (Added Fee) — Roundtables PM Roundtable Discussion
Section on Statistical Computing
Organizer(s): Kary Myers, Los Alamos National Laboratory
WL13:	Wearables, Digital Medicine and Data Science Dandan Wang, Faculty of Health Sciences, Univerity of Macau; Xiaohua Douglas Zhang, University of Macau

544 * !	Wed, 7/31/2019, 2:00 PM - 3:50 PM	CC-506
Dynamic Graphical Models and Networks with Applications — Invited Papers
International Indian Statistical Association, Section on Statistical Learning and Data Science, Section on Statistical Computing
Organizer(s): Sharmodeep Bhattacharyya, Oregon State University
Chair(s): Sharmodeep Bhattacharyya, Oregon State University
2:05 PM	Mixed Membership Stochastic Blockmodels for Heterogeneous Networks Yuguo Chen, University of Illinois at Urbana-Champaign
2:20 PM	On the CUSUM Changepoint Estimator for Network Data Shirshendu Chatterjee, City University of New York, City College; Sharmodeep Bhattacharyya, Oregon State University; Peter J Bickel, University of California, Berkeley; Soumendu Sundar Mukherjee, Indian statistical Institute
2:35 PM	Inference in Vector Autoregressive Models with Union of Intersections for Sparse, Accurate, and Predictive Dynamic Causal Networks at Scale Kristofer Bouchard, Lawrence Berkeley National Laboratory
2:50 PM	Network Modeling of High-Dimensional Time Series Sumanta Basu, Cornell University
3:05 PM	Discussant: Peter J Bickel, University of California, Berkeley
3:20 PM	Discussant: Sofia C Olhede, University College London
3:25 PM	Floor Discussion

545 * !	Wed, 7/31/2019, 2:00 PM - 3:50 PM	CC-607
Towards Perfect and Scalable Distributional Computation — Invited Papers
IMS, International Society for Bayesian Analysis (ISBA), Section on Statistical Computing
Organizer(s): Xiao-Li Meng, Harvard University
Chair(s): David Jones, Texas A&M University
2:05 PM	Exact Estimation with Markov Chain Monte Carlo Presentation Aguemon Yves Atchade, Boston University; Xiao-Li Meng, Harvard University
2:30 PM	The Never-Ending MCMC Revolution: Making Dempster-Shafer Modeling Practical Presentation Ruobin Gong, Rutgers University; Xiao-Li Meng, Harvard University
2:55 PM	Fiducial Selector: Scalable Statistical Inference for High-Dimensional Regression Problems Thomas C. M. Lee, UC Davis; Jan Hannig, UNC Chapel Hill; Randy Lai, U of Maine; Chunzhe Zhang, UC Davis
3:20 PM	Discussant: Keli Liu, Stanford University
3:45 PM	Floor Discussion

546 !	Wed, 7/31/2019, 2:00 PM - 3:50 PM	CC-501
Recent Advances in Time Series and Point Process — Invited Papers
Business and Economic Statistics Section, Section on Risk Analysis, Section on Statistical Computing
Organizer(s): Xialu Liu, San Diego State University
Chair(s): Xialu Liu, San Diego State University
2:05 PM	A Factor Model Approach for High-Dimensional Dynamic Tensor Time Series Rong Chen, Rutgers University; Dan Yang, Rutgers University; Cun-Hui Zhang, Rutgers University
2:30 PM	A Bivariate Point Process Model with Application to Social Media User Content Generation Yongtao Guan, University of Miami
2:55 PM	Time Series Forecasting with Random Forests and Nonparametric Models Barbara Ann Bailey, San Diego State University
3:20 PM	A Class of Generalized Self-Normalizers for Inference of Time Series and Its Optimal Weighting Ting Zhang, Boston University
3:45 PM	Floor Discussion

550 * !	Wed, 7/31/2019, 2:00 PM - 3:50 PM	CC-605
Statistics on Street Corners — Invited Papers
Section on Statistical Graphics, Section on Statistical Computing, Section on Bayesian Statistical Science
Organizer(s): Dianne Cook, Monash University
Chair(s): Heike Hofmann, Iowa State University
2:05 PM	Visual Inference for Model Checking Presentation Adam Loy, Carleton College; Heike Hofmann, Iowa State University; Dianne Cook, Monash University
2:20 PM	Can You Become Skillful Over Time to Influence Visual Inference Presentation Mahbubul Majumder, University of Nebraska at Omaha; Dianne Cook, Monash University; Heike Hofmann, Iowa State University
2:35 PM	Deep Visual Inference: Teaching Computers to See Rather Than Calculate Correlation Presentation Giora Simchoni, vFunction
2:50 PM	Statistical Lineups for Bayesians Presentation Susan Vanderplas, Iowa State University; Heike Hofmann, Iowa State University
3:05 PM	Discussant: Hadley Wickham, RStudio
3:35 PM	Floor Discussion

559 !	Wed, 7/31/2019, 2:00 PM - 3:50 PM	CC-301
Randomized Algorithms for Optimization Problems in Statistics — Topic Contributed Papers
Section on Statistical Learning and Data Science, IMS, Section on Statistical Computing
Organizer(s): Miles Lopes, UC Davis
Chair(s): Miles Lopes, UC Davis
2:05 PM	Statistical Properties of Stochastic Gradient Descent Presentation Panagiotis Toulis, University of Chicago Booth School of Business; Jerry Chee, University of Chicago
2:25 PM	Randomized Sparse PCA Using the Variable Projection Method N. Benjamin Erichson, Univ of California - Berkeley
2:45 PM	Randomized Linear Algebra and Its Applications in Second-Order Optimization and Deep Learning Presentation Zhewei Yao, UC Berkeley
3:05 PM	Understanding the Acceleration Phenomenon via High-Resolution Differential Equations Weijie Su, University of Pennsylvania
3:25 PM	Random Projections for Faster Non-Convex Optimization Mert Pilanci, Stanford University

574	Wed, 7/31/2019, 2:00 PM - 3:50 PM	CC-302
Recent Advances in Software — Contributed Papers
Section on Statistical Computing, Text Analysis Interest Group
Chair(s): Julie Bessac, Argonne National Laboratory
2:05 PM	ICBayes: a Package for Bayesian Semiparametric Regression Analysis of Interval-Censored Data Chun Pan, Hunter College; Bo Cai, University of South Carolina; Lianming Wang, University of South Carolina; Xiaoyan Lin, University of South Carolina
2:20 PM	The Fundamental Instruction Set Operation Codes Support Function Library Presentation Timothy Hall, PQI Consulting
2:35 PM	Analytical Likelihood Derivatives for State Space Forecasting Models Jonathan Hosking, Amazon.com; Ramesh Natarajan, Amazon.com
2:50 PM	Graph Matching Algorithms Using the IGraphMatch R Package Zihuan Qiao; Daniel L Sussman, Boston University
3:05 PM	Language Modeling Using SAS JeeHyun Hwang, SAS Institute Inc.; Xu Yang, SAS Institute Inc.; Haipeng Liu, SAS Institute Inc.
3:20 PM	Analyzing Interval-Valued Spatial Data in the Intkrige R Package Presentation Brennan Bean
3:35 PM	Floor Discussion

585 * !	Thu, 8/1/2019, 8:30 AM - 10:20 AM	CC-102
Exploiting Latent Structure for Network Inference — Invited Papers
Section on Statistical Computing, Section on Statistical Learning and Data Science, Section on Bayesian Statistical Science
Organizer(s): Avanti Athreya, Johns Hopkins University
Chair(s): Minh Tang, Johns Hopkins University
8:35 AM	Leveraging Exchangeability Assumptions to Make Inference in Regression with Network Outcomes Bailey Fosdick, Colorado State University
9:00 AM	Overlapping Clustering Models, and One (Class) SVM to Bind Them All. Purnamrita Sarkar, University of Texas, Austin
9:25 AM	'Statistics 101' for Network Data Objects Eric Kolaczyk, Boston University
9:50 AM	Consistency in Vertex Nomination Vince Lyzinski, University of Massachusetts Amherst
10:15 AM	Floor Discussion

616	Thu, 8/1/2019, 8:30 AM - 10:20 AM	CC-104
Multidisciplinary Advances in Computing — Contributed Papers
Section on Statistical Computing
Chair(s): Anirban Mondal, Case Western Reserve University
8:35 AM	On the Fractional Moments of a Truncated Centered Multivariate Normal Distribution Mitsunori Ogawa, The University of Tokyo; Kazuki Nakamoto, Keio University; Tomonari Sei, The University of Tokyo
8:50 AM	Applications of Quantum Annealing in Statistics Presentation Robert Foster, Los Alamos National Laboratory
9:05 AM	Nearly Best Wald Confidence Intervals Presentation George Terrell, VA Poly. Inst. & State Univ.
9:20 AM	Noncentral Algorithm Assessments Jerry Lewis, Biogen Idec
9:35 AM	Distance-Distributed Design for Gaussian Process Surrogates Presentation Boya Zhang, Virginia Tech; Robert Gramacy, Virginia Tech
9:50 AM	A Simple and Fast Divide-And-Conquer Approach in Multivariate Survival Analysis Presentation Wei Wang, Rutgers University Department of Biostatistics and Epidemiology; Shou-En Lu, Rutgers University Department of Biostatistics and Epidemiology; Jerry Q. Cheng, Rutgers University Office of Advanced Research Computing
10:05 AM	A Most Informative Index of Severity of Mental Health Presentation Barbara Clothier, CCDOR-Mpls VAHCS; Maureen Murdoch, CCDOR-Mpls VAHCS and University of MN; Siamak Noorbaloochi, CCDOR-Mpls VAHCS and University of MN

645 * !	Thu, 8/1/2019, 10:30 AM - 12:20 PM	CC-107
Bayesian Optimization — Topic Contributed Papers
Section on Bayesian Statistical Science, Section on Statistical Computing, International Society for Bayesian Analysis (ISBA)
Organizer(s): Tony Pourmohamad, Genentech
Chair(s): Jasper Snoek, Google Brain
10:35 AM	The Statistical Filter Approach to Constrained Optimization Herbert Lee, Univ of California, Santa Cruz
10:55 AM	Bayesian Optimization via Barrier Functions Presentation Tony Pourmohamad, Genentech; Herbert Lee, Univ of California, Santa Cruz
11:15 AM	Bayesian Optimization for Policy Search via Online-Offline Experimentation Eytan Bakshy, Facebook; Benjamin Letham, Facebook
11:35 AM	Automating Bayesian Optimization with Bayesian Optimization Presentation Roman Garnett, Washington Univeristy in St. Louis; Gustavo Malkomes, Washington University in St. Louis
11:55 AM	Bayesian Optimization for Robotics Presentation Roberto Calandra, Facebook AI Research
12:15 PM	Floor Discussion

650 * !	Thu, 8/1/2019, 10:30 AM - 12:20 PM	CC-501
Quantum Computing: Optimization Algorithms and Applications — Topic Contributed Papers
Section on Statistical Computing, Biometrics Section, Biopharmaceutical Section
Organizer(s): Sergei Leonov, CSL Behring
Chair(s): James Wendelberger, Los Alamos National Laboratory and University of New Mexico
10:35 AM	Quantum Computing in the Life Sciences Mark Fingerhuth, ProteinQure
10:55 AM	Treasure Hunt for Computational Problems That Can Be Solved Faster by Quantum Annealing Presentation Barry Sanders, University of Calgary; Archismita Dalal, University of Calgary; Radhakrishnan Balu, United States Army Research Laboratory
11:15 AM	Quantum Computing at Lockheed Martin Kristen Pudenz
11:35 AM	Optimization Algorithms of Model-Based Design: Simulated Vs Quantum Annealing Presentation 1 Presentation 2 Valerii Fedorov, ICONplc
11:55 AM	Discussant: Sergei Leonov, CSL Behring
12:15 PM	Floor Discussion

JSM 2019 Online Program

Activity Details

American Statistical Association