Optic Flow Field Segmentation and Motion Estimation Using a Robust Genetic Partitioning Algorithm. - Yan Huang 010; Kannappan Palaniappan; Xinhua Zhuang; Joseph E. Cavanaugh (IEEE Trans. Pattern Anal. Mach. Intell., 1995)

An autoregressive model for analysis of ice sheet elevation change time series. - Adam C. Ferguson; Curt H. Davis; Joseph E. Cavanaugh (IEEE Trans. Geosci. Remote. Sens., 2004)

An improved Akaike information criterion for state-space model selection. - Thomas Bengtsson; Joseph E. Cavanaugh (Comput. Stat. Data Anal., 2006)

Bootstrap variants of the Akaike information criterion for mixed model selection. - Junfeng Shang; Joseph E. Cavanaugh (Comput. Stat. Data Anal., 2008)

Performance of Variable Selection Methods in Regression Using Variations of the Bayesian Information Criterion. - Tom Burr; Herb Fry; Brian McVey; Eric Sander; Joseph E. Cavanaugh; Andrew A. Neath (Commun. Stat. Simul. Comput., 2008)

Akaike's Information Criterion: Background, Derivation, Properties, and Refinements. - Joseph E. Cavanaugh; Andrew A. Neath (International Encyclopedia of Statistical Science, 2011)

Multiple Comparisons Testing from a Bayesian Perspective. - Andrew A. Neath; Joseph E. Cavanaugh (International Encyclopedia of Statistical Science, 2011)

Model evaluation, discrepancy function estimation, and social choice theory. - Andrew A. Neath; Joseph E. Cavanaugh; Adam G. Weyhaupt (Comput. Stat., 2015)

A multistage algorithm for best-subset model selection based on the Kullback-Leibler discrepancy. - Tao Zhang 092; Joseph E. Cavanaugh (Comput. Stat., 2016)

Model selection criteria based on cross-validatory concordance statistics. - Patrick Ten Eyck; Joseph E. Cavanaugh (Comput. Stat., 2018)

Extending AIC to best subset regression. - J. G. Liao; Joseph E. Cavanaugh; Timothy L. McMurry (Comput. Stat., 2018)

Forensics: Assessing model goodness: A machine learning view. - Joseph R. Barr; Joseph E. Cavanaugh (Encycl. Semantic Comput. Robotic Intell., 2018)

Agglomerative and divisive hierarchical Bayesian clustering. - Elliot Burghardt; Daniel K. Sewell; Joseph E. Cavanaugh (Comput. Stat. Data Anal., 2022)

Probabilistic Pairwise Model Comparisons Based on Bootstrap Estimators of the Kullback-Leibler Discrepancy. - Andres Dajles; Joseph E. Cavanaugh (Entropy, 2022)

A comprehensive framework to estimate the frequency, duration, and risk factors for diagnostic delays using bootstrapping-based simulation methods. - Aaron C. Miller; Joseph E. Cavanaugh; Alan T. Arakkal; Scott H. Koeneman; Philip M. Polgreen (BMC Medical Informatics Decis. Mak., 2023)

Bootstrap Approximation of Model Selection Probabilities for Multimodel Inference Frameworks. - Andres Dajles; Joseph E. Cavanaugh (Entropy, 2024)

Can a Transparent Machine Learning Algorithm Predict Better than Its Black Box Counterparts? A Benchmarking Study Using 110 Data Sets. - Ryan A. Peterson; Max McGrath; Joseph E. Cavanaugh (Entropy, 2024)

Assessing Variable Importance for Best Subset Selection. - Jacob Seedorff; Joseph E. Cavanaugh (Entropy, 2024)

A new class of information criteria for improved prediction in the presence of training/validation data heterogeneity. - Javier E. Flores; Joseph E. Cavanaugh; Andrew A. Neath (Comput. Stat., 2025)