444
Thu, 8/12/2021,
4:00 PM -
5:50 PM
Virtual
Recent Advances in Statistical Methodology for Big Data — Contributed Speed
IMS
Chair(s): Zhimei Ren, Stanford University
4:05 PM
Bayesian Generalized Linear Model for Difference of Over or Under Dispersed Counts
Andrew W Swift, University of Nebraska at Omaha ; Kimberly Sellers, Georgetown University / U.S. Census Bureau
4:10 PM
An Efficient Monte Carlo EM Algorithm for Estimating Heterogenous Crossed Effects in GLMM
Rashmi Ranjan Bhuyan, University of Southern California ; Gourab Mukherjee, University of Southern California; Wreetabrata Kar, Purdue University
4:15 PM
Learning Trends of COVID-19 Using Semi-Supervised Clustering
Semhar Michael, South Dakota State University
4:20 PM
Weak Convergence of Reversed Martingales to Mixtures of Brownian Motions
Mohamed Amezziane, Central Michigan University ; Ibrahim Ahmad, Oklahoma State University
4:25 PM
Population Interference in Panel Experiments
Kevin Wu Han, Department of Statistics, Stanford University ; Iavor Bojinov, Harvard Business School; Guillaume Basse, Department of MS&E and Department of Statistics, Stanford University
4:30 PM
Joint and Individual Variations of Sleep, Physical Activity, and Circadian Rhythmicity Features in CoLaus Study
Sun J Kang, National Institutes of Health ; Andrew Leroux, University of Colorado Anschutz Medical Campus; Wei Guo, National Institutes of Health; Martin Preisig, University Hospital of Lausanne; Kathleen Merikangas, National Institute of Mental Health; Vadim Zipunnikov, Johns Hopkins Bloomberg School of Public Health
4:35 PM
Some Results on Identifiable Parameters That Cannot Be Identified from Data, Including Constant Correlation Between Gaussian Observations
Christian Hennig, University of Bologna
4:40 PM
On Measuring Model Complexity in Heteroskedastic Linear Regression
Bo Luan, The Ohio State University ; Yoonkyung Lee, Ohio State University; Yunzhang Zhu, Ohio State University
4:45 PM
Density Deconvolution with Nonstandard Error Distributions: Rates of Convergence and Adaptive Estimation
Taeho Kim, University of Haifa
4:55 PM
The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference Across Multiple Networks
Konstantinos Pantazis, Department of Mathematics ; Avanti Athreya, Department of Applied Mathematics and Statistics; Vince Lyzinski, University of Maryland; Jesus Arroyo Relión, Texas A&M University, Department of Statitics; William N. Frost, Cell Biology and Anatomy, and Center for Brain Function and Repair; Evan S. Hill, Cell Biology and Anatomy, and Center for Brain Function and Repair
5:00 PM
Simultaneous Inference for the Common and Idiosyncratic of the Dynamic Factor Model
Yuanyuan Zhang, Soochow University ; Jiangyan Wang, Nanjing Audit University; Xinbing Kong, Nanjing Audit University
5:05 PM
ZAP: Z-Value-Based Covariate-Adaptive Multiple Testing
Dennis Leung, University of Melbourne
5:10 PM
A Central Limit Theorem for the Benjamini-Hochberg False Discovery Proportion Under a Factor Model
Dan M. Kluger, Stanford University ; Art Owen, Stanford University
5:15 PM
Free-Knot Spline and Its Confidence Bands for Generalized Regression Models
Elena Elisa Graetz, University of Illinois at Chicago ; Jing Elisa Wang, University of Illinois at Chicago
5:20 PM
Fast and Scalable SPCA via Statistical Modeling Reductions
Kayhan Behdin, MIT ; Rahul Mazumder, Massachusetts Institute of Technology
5:25 PM
The Parametric Weight Functions for the Analysis of Size-Biased Data Using the Weighted Lognormal Distribution and Related Estimation Procedures
Makarand V Ratnaparkhi, Wright State University
5:30 PM
Convergence Rates of Two-Component MCMC Samplers
Qian Qin, University of Minnesota ; Galin Jones, University of Minnesota
5:35 PM
Quantifying Rounding-Induced Error for Non-Negative Discrete Random Variables
Axel Cortes Cubero, University of Puerto Rico at Mayaguez ; Roberto Reyes, University of Puerto Rico at Mayaguez; Wolfgang Rolke, University of Puerto Rico at Mayaguez
5:40 PM
Floor Discussion
