2 papers
stat.ME2026
Measuring Neural Network Complexity via Effective Degrees of Freedom
Jia Zhou, Douglas Landsittel
Quantifying the complexity of feed-forward neural networks (FFNNs) remains challenging due to their nonlinear, hierarchical structure and numerous parameters. We apply generalized…
stat.ME2025
A Relativity-Based Framework for Statistical Testing Guided by the Independence of Ancillary Statistics: Methodology and Nonparametric Illustrations
Albert Vexler, Douglas Landsittel
This paper introduces a decision-theoretic framework for constructing and evaluating test statistics based on their relationship with ancillary statistics-quantities whose distribu…