Sharon, Author at International Indian Statistical Association

Topics in theoretical statistics and Applied Probability

Organizer: Parthanil Roy, Indian Statistical Institute
Chair: Srinivasan Balaji, George Washington University
Time: Saturday, 16:30–18:00
Room: LInC 314

16:30-17:00

How Being Distributionally Robust Can Improve Learning In High Dimensions?

Karthyek Murthy, Columbia University

17:00-17:30

Optimal design and subdata selection for big data

John Stufken, Arizona State University

17:30-18:00

Stationarity as a Path Property–with Applications in Time Series Analysis

Yi Shen, University of Waterloo

Time: 18:00–19:30
Location: CH2M HILL Alumni Center

Wine bar sponsored by the Oregon State University College of Science.

Data Analysis of Adverse Reaction of Pandemic Vaccines among USA in 2013

Chenxiao Hu, Oregon State University

Rate of Convergence for Maximum Likelihood Estimation for Mixture of Uniform Densities

Nilanjana Laha, University of Washington

Two-Stage Method in Anomaly Detection Using Isolation Tree

Si Liu, Oregon State University

Skewing Methods for a variance-stabilizing locally linear regression estimator

Kiheiji Nishida, Hyogo University of Health Science, Japan

Link Misspecification in Binary Regression

Evrim Oral, LSUHSC School of Public Health Biostatistics Program

Matrix-free computation for spatial-temporal Gaussian autoregressive model using Kalman filter and h-likelihood method

ChunXiao Wang, Oregon State University

Probability theory and networks

Organizer: Po-Ling Loh, University of Pennsylvania
Chair: Sharmodeep Bhattacharyya, Oregon State University
Time: Sunday, 8:00–9:30
Room: LInC 314

8:00-8:30

Power of graph-based two-sample tests

Bhaswar Bhattacharya, Stanford University

8:30-9:00

Persistence of centrality in random growing trees

Varun Jog, University of Pennsylvania

9:00-9:30

Computing and maximizing influence in linear threshold and triggering models

Po-Ling Loh, University of Wisconsin, Madison

Recent advances in time series and spatial analysis

Organizer: Lan Xue, Oregon State University
Chair: Lan Xue, Oregon State University
Time: Sunday, 8:00–9:30
Room: LInC 302

8:00-8:30

Bivariate Penalized Splines for Geo-Spatial Regression

Lily Wang, Iowa State University

8:30-9:00

Robust estimation of conditional variance of time series using density power divergences

T.N. Sriram, University of Georgia

9:00-9:30

Multivariate Functional Data Analysis for Dynamic Biomedical Imaging

Yuan Wang, Washington State University

Statistical Innovation in Biomedical Sciences

Organizer: Lei Shu, Astellas Pharma US, Inc
Chair: Saonli Basu, University of Minnesota
Time: Sunday, 8:00–9:30
Room: LInC368

8:00-8:30

On Detection of “Sparse Signals”

Rajarshi Mukherjee, Stanford University

8:30-9:00

Statistical Methods for Public Health and Medicine

Haikady Nagaraja, The Ohio State University

9:00-9:30

Issues & Challenges in Diabetes Drug Development

Shailaja Suryawanshi, Merck and Co.

Statistical Inference for High Dimensional Data

Organizer: Soumen Lahiri, North Carolina State University
Chair: Xiaohui Chang, Oregon State University
Time: Sunday, 8:00–9:30
Room: LInC 345

8:00-8:30

Partially Penalized Regression for High Dimensional Data

Peng Yang, North Carolina State University

8:30-9:00

Compressed Sensing without Sparsity Assumptions

Miles Lopes, University of California, Davis

9:00-9:30

Estimation and Inference in High Dimensional Linear Models with Measurement Error and Missing Covariate

Abhishek Kaul, National Institute of Environmental Health Sciences

Contributed Session 1

Organizer: IISA
Chair: T. Krishna Kumar, Rockville-Analytics
Time: Sunday, 8:00–9:30
Room: LInC 268

8:00-8:15

Learning Nonparametric Regression Using Gaussian Processes with Missing Covariate

Abhishek Bishoyi, University of Connecticut

8:15–8:30

Multivariate Spectral Variance Estimators in Markov Chain Monte Carlo

Dootika Vats, University of Minnesota

8:30-8:45

Sufficient variable selection via an independence index

Qingcon Yuan, University of Kentucky

8:45-9:00

A study on pre ovular and post ovular day counts and their association with time to pregnancy under joint modeling paradigm

Somak Chatterjee, George Washington University

9:00-9:15

Robust Weighted LAD-Adaptive group-LASSO for Functional Regression Model

Jasdeep Pannu, Lamar University

9:15-9:30

Singular values and Odds ratios- a comparative study

Alfrad Nobel Bhuiyan, University of Cincinnati

Randomized Response Models

Organizer: Sat Gupta, University of North Carolina, Greensboro
Chair: John Stufken, Arizona State University
Time: Sunday, 10:00–11:30
Room: LInC 314

10:00-10:30

A Statistical Approach to Privacy Preserving Data Publishing

Tapan Nayak, George Washington University

10:30-11:00

A New Two-Stage Sampling Design for Sensitive Questions through Randomized Response Technique and Direct Questioning

Evrim Oral, Louisiana State University Health Sciences Center New Orleans

11:00-11:30

Data Confidentiality and Respondent Privacy Protection

Sat Gupta, University of North Carolina–Greensboro

Statistics for complex data structures

Organizer: Soumen Lahiri, North Carolina State University
Chair: Abhishek Kaul, National Institute of Environmental Health Sciences
Time: Sunday, 10:00–11:30
Room: LInC 268

10:00-10:30

Analysis of linear transformation models with errors-in-covariates and interval censoring

Samiran Sinha, Texas A&M University

10:30-11:00

Spatiotemporal mixed modeling of multisubject fMRI

Benjamin Risk, SAMSI and University of North Carolina, Chapel Hill

11:00-11:30

A smoothed bootstrap method for time series quantile regression

Dan Nordman, Iowa State University

New directions in network analysis

Organizer: Purnamrita Sarkar, UT Austin
Chair: Po-Ling Loh, University of Wisconsin, Madison
Time: Sunday, 10:00–11:30
Room: LInC 302

Topics in theoretical statistics and Applied Probability

16:30-17:00

How Being Distributionally Robust Can Improve Learning In High Dimensions?

17:00-17:30

Optimal design and subdata selection for big data

17:30-18:00

Stationarity as a Path Property–with Applications in Time Series Analysis

Data Analysis of Adverse Reaction of Pandemic Vaccines among USA in 2013

Rate of Convergence for Maximum Likelihood Estimation for Mixture of Uniform Densities

Two-Stage Method in Anomaly Detection Using Isolation Tree

Skewing Methods for a variance-stabilizing locally linear regression estimator

Link Misspecification in Binary Regression

Matrix-free computation for spatial-temporal Gaussian autoregressive model using Kalman filter and h-likelihood method

Probability theory and networks

8:00-8:30

Power of graph-based two-sample tests

8:30-9:00

Persistence of centrality in random growing trees

9:00-9:30

Computing and maximizing influence in linear threshold and triggering models

Recent advances in time series and spatial analysis

8:00-8:30

Bivariate Penalized Splines for Geo-Spatial Regression

8:30-9:00

Robust estimation of conditional variance of time series using density power divergences

9:00-9:30

Multivariate Functional Data Analysis for Dynamic Biomedical Imaging

Statistical Innovation in Biomedical Sciences

8:00-8:30

On Detection of “Sparse Signals”

8:30-9:00

Statistical Methods for Public Health and Medicine

9:00-9:30

Issues & Challenges in Diabetes Drug Development

Statistical Inference for High Dimensional Data

8:00-8:30

Partially Penalized Regression for High Dimensional Data

8:30-9:00

Compressed Sensing without Sparsity Assumptions

9:00-9:30

Estimation and Inference in High Dimensional Linear Models with Measurement Error and Missing Covariate

Contributed Session 1

8:00-8:15

Learning Nonparametric Regression Using Gaussian Processes with Missing Covariate

8:15–8:30

Multivariate Spectral Variance Estimators in Markov Chain Monte Carlo

8:30-8:45

Sufficient variable selection via an independence index

8:45-9:00

A study on pre ovular and post ovular day counts and their association with time to pregnancy under joint modeling paradigm

9:00-9:15

Robust Weighted LAD-Adaptive group-LASSO for Functional Regression Model

9:15-9:30

Singular values and Odds ratios- a comparative study

Randomized Response Models

10:00-10:30

A Statistical Approach to Privacy Preserving Data Publishing

10:30-11:00

A New Two-Stage Sampling Design for Sensitive Questions through Randomized Response Technique and Direct Questioning

11:00-11:30

Data Confidentiality and Respondent Privacy Protection

Statistics for complex data structures

10:00-10:30

Analysis of linear transformation models with errors-in-covariates and interval censoring

10:30-11:00

Spatiotemporal mixed modeling of multisubject fMRI

11:00-11:30

A smoothed bootstrap method for time series quantile regression

New directions in network analysis

10:00-10:30

Network modeling of topological domains using Hi-C data

10:30-11:00

Title TBD

11:00-11:30

Unbiased Estimation of Causal Effects under Network Interference

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