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Contributed Papers

Nonparametric and Semiparametric Modeling and Inference

Mon, Aug 3, 8:30 AM - 10:20 AM Room CC-256 Thomas M. Menino Convention & Exhibition Center

Jialin ZhangChair

Section on Nonparametric Statistics

7 Presentations

Confidence Intervals for Comparing Two Correlated Inverse Coefficients of Variation

8:35 AM - 8:50 AM

Inverse coefficient of variation Confidence intervals Skewed distributions Nonparametric methods Adjusted asymptotic approach Likelihood-based methods

Kernel-Weighted Deep Neural Networks for Sparse and Irregular Longitudinal Prediction

8:50 AM - 9:05 AM

Seonjin Kim (Miami University)

Co-authors: David Cirkovic (Miami University)

Deep neural networks kernel weighting Longitudinal data analysis

Possibilistic Inferential Models for Gaussian Mixture Models: Inference and Prediction

9:05 AM - 9:20 AM

James Robertson

Co-authors: Ryan Martin

Model Selection Valid Exact Coverage Finite Sample Density Estimation

Residual-Based Subdata Selection for Local Regression and Its Extension to Partial Linear Model

9:20 AM - 9:35 AM

Chia-Wei Lin (Institute of Statistics and Data Science, National Tsing Hua University, Taiwan)

Co-authors: Li-Shan Huang (National Tsing Hua University, Taiwan)

Local linear regression Subdata selection Partial linear model Nonparametric regression L1 convergence

Semiparametric Robust Zero-Altered Models for Regression Analysis of Count Data

9:35 AM - 9:50 AM

Co-authors: Sujit Ghosh (North Carolina State University), Kimberly Sellers (North Carolina State University)

Generalized method of moments over-dispersion under-dispersion misspecification excess zeroes semiparametric methods

Source-Condition Analysis of Kernel Adversarial Estimators

9:50 AM - 10:05 AM

Antonio Olivas-Martinez (University of Pennsylvania)

Co-authors: Andrea Rotnitzky (University of Washington)

Finite Error Bounds Integral Equations Kernel Adversarial Estimators of Moment Equations Mini-max Learning Reproducing Kernel Hilbert Spaces Source Condition

Starshaped Mean Residual Life Modeling of Rural STEM Teacher Retention

10:05 AM - 10:20 AM

mohammad sepehrifar

mean residual life survival analysis Bayesian methods teacher retention rural STEM education PMRL regression

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