2 citations · 2 across the 9 of their papers we have counts for
10 papers
Generalized Fiducial Inference for Hybrid Discrete-Continuous Count Data: Theory and Application
Kendall Thomas, Jan Hannig
High-frequency athlete-tracking data can be summarized as quantile cubes (Thomas and Hannig, 2026): counts of time spent in bins of velocity, acceleration, and movement angle. In o…
Advanced Distribution Theory for Significance in Scale Space
Rui Liu, Jan Hannig, J. S. Marron
Smoothing methods find signals in noisy data. A challenge for Statistical inference is the choice of smoothing parameter. SiZer addressed this challenge in one-dimension by detecti…
Bayesian Forensic DNA Mixture Deconvolution Using a Novel String Similarity Measure
Taylor Petty, Jan Hannig, Hari Iyer
Mixture interpretation is a central challenge in forensic science, where evidence often contains contributions from multiple sources. In the context of DNA analysis, biological sam…
Evaluating Gender Wage Inequality in Academia using Causal Inference Methods for Observational Data
Zihan Zhang, Jan Hannig
Observational studies often present challenges for causal inference due to confounding and heterogeneity. In this paper, we illustrate how modern causal inference methods can be ap…
Movement Dynamics in Elite Female Soccer Athletes: The Quantile Cube Approach
Kendall L. Thomas, Jan Hannig
This paper presents the quantile cube, a novel three-dimensional summary representation designed to analyze external load using GPS-derived movement data. While broadly applicable,…
Elastic Shape Analysis of Movement Data
J. E. Borgert, Jan Hannig, J. D. Tucker +6
Osteoarthritis (OA) is a highly prevalent degenerative joint disease, and the knee is the most commonly affected joint. Biomechanical factors, particularly forces exerted during wa…
Multi-faceted Neuroimaging Data Integration via Analysis of Subspaces
Andrew Ackerman, Zhengwu Zhang, Jan Hannig +2
Neuroimaging studies, such as the Human Connectome Project (HCP), often collect multi-faceted and multi-block data to study the complex human brain. However, these data are often a…
AutoGFI: Streamlined Generalized Fiducial Inference for Modern Inference Problems in Models with Additive Errors
Wei Du, Jan Hannig, Thomas C. M. Lee +2
The concept of fiducial inference was introduced by R. A. Fisher in the 1930s to address the perceived limitations of Bayesian inference, particularly the need for subjective prior…
Dempster-Shafer P-values: Thoughts on an Alternative Approach for Multinomial Inference
Kentaro Hoffman, Kai Zhang, Tyler McCormick +1
In this paper, we demonstrate that a new measure of evidence we developed called the Dempster-Shafer p-value which allow for insights and interpretations which retain most of the s…
A Bernstein-von Mises Theorem for Generalized Fiducial Distributions
J. E. Borgert, Jan Hannig
An established and growing literature on generalized fiducial inference and related fiducial ideas points to the adoption of fiducial inference as a mainstream perspective among mo…