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
