Howard Bondell

Variational Bayes for Fast and Accurate Empirical Likelihood Inference

Weichang Yu, Howard D Bondell

Journal article  |  2023  |  JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

We develop a fast and accurate approach to approximate posterior distributions in the Bayesian empirical likelihood framework. Bay..

Correction: Nonparametric conditional density estimation in a deep learning framework for short-term forecasting (Environmental and Ecological Statistics, (2022), 29, 4, (677-704), 10.1007/s10651-021-00499-z)

DB Huberman, BJ Reich, HD Bondell

Journal article  |  2022  |  Environmental and Ecological Statistics

An incomplete version of this article was published May 2021. It has been updated to include all text. The original article has be..

Nonstationary Gaussian Process Discriminant Analysis With Variable Selection for High-Dimensional Functional Data

Weichang Yu, Sara Wade, Howard D Bondell, Lamiae Azizi

Journal article  |  2022  |  JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS

High-dimensional classification and feature selection tasks are ubiquitous with the recent advancement in data acquisition technol..

A representation learning framework for detection and characterization of dead versus strain localization zones from pre-to post-failure

Antoinette Tordesillas, Shuo Zhou, James Bailey, Howard Bondell

Journal article  |  2022  |  GRANULAR MATTER

Abstract: Experiments have long shown that zones of near vanishing deformation, so-called “dead zones”, emerge and coexist with st..

Temporal and spectral governing dynamics of Australian hydrological streamflow time series

Nick James, Howard Bondell

Journal article  |  2022  |  JOURNAL OF COMPUTATIONAL SCIENCE

We use new and established methodologies in multivariate time series analysis to study the dynamics of 414 Australian hydrological..

On robust probabilistic principal component analysis using multivariate t-distributions

Yiping Guo, Howard Bondell

Journal article  |  2022  |  COMMUNICATIONS IN STATISTICS-THEORY AND METHODS

Probabilistic principal component analysis (PPCA) is a probabilistic reformulation of principal component analysis (PCA), under th..

In search of peak human athletic potential: A mathematical investigation

Nick James, Max Menzies, Howard Bondell

Journal article  |  2022  |  CHAOS

This paper applies existing and new approaches to study trends in the performance of elite athletes over time. We study both track..

Comparing the dynamics of COVID-19 infection and mortality in the United States, India, and Brazil

Nick James, Max Menzies, Howard Bondell

Journal article  |  2022  |  PHYSICA D-NONLINEAR PHENOMENA

This paper compares and contrasts the spread and impact of COVID-19 in the three countries most heavily impacted by the pandemic: ..

Uncertainty Quantification in Depth Estimation via Constrained Ordinal Regression

Dongting Hu, Liuhua Peng, Tingjin Chu, Xiaoxing Zhang, Yinian Mao, Howard Bondell, Mingming Gong

Book Chapter  |  2022  |  Lecture Notes in Computer Science

Monocular Depth Estimation (MDE) is a task to predict a dense depth map from a single image. Despite the recent progress brought b..

Spatial Confounding in Generalized Estimating Equations

Francis KC Hui, Howard D Bondell

Journal article  |  2021  |  AMERICAN STATISTICIAN

Spatial confounding, where the inclusion of a spatial random effect introduces multicollinearity with spatially structured covaria..