Joseph E. Cavanaugh

According to our database, Joseph E. Cavanaugh authored at least 18 papers between 1995 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Assessing Variable Importance for Best Subset Selection.

Jacob Seedorff, Joseph E. Cavanaugh

Entropy, September, 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, September, 2024

Bootstrap Approximation of Model Selection Probabilities for Multimodel Inference Frameworks.

Andres Dajles, Joseph E. Cavanaugh

Entropy, July, 2024

2023

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., December, 2023

2022

Probabilistic Pairwise Model Comparisons Based on Bootstrap Estimators of the Kullback-Leibler Discrepancy.

Andres Dajles, Joseph E. Cavanaugh

Entropy, 2022

Agglomerative and divisive hierarchical Bayesian clustering.

Elliot Burghardt, Daniel K. Sewell, Joseph E. Cavanaugh

Comput. Stat. Data Anal., 2022

2018

Forensics: Assessing model goodness: A machine learning view.

Joseph R. Barr, Joseph E. Cavanaugh

Encycl. Semantic Comput. Robotic Intell., 2018

Extending AIC to best subset regression.

J. G. Liao, Joseph E. Cavanaugh, Timothy L. McMurry

Comput. Stat., 2018

Model selection criteria based on cross-validatory concordance statistics.

Patrick Ten Eyck, Joseph E. Cavanaugh

Comput. Stat., 2018

2016

A multistage algorithm for best-subset model selection based on the Kullback-Leibler discrepancy.

Tao Zhang, Joseph E. Cavanaugh

Comput. Stat., 2016

2015

Model evaluation, discrepancy function estimation, and social choice theory.

Andrew A. Neath, Joseph E. Cavanaugh, Adam G. Weyhaupt

Comput. Stat., 2015

2011

Multiple Comparisons Testing from a Bayesian Perspective.

Andrew A. Neath, Joseph E. Cavanaugh

Proceedings of the International Encyclopedia of Statistical Science, 2011

Akaike's Information Criterion: Background, Derivation, Properties, and Refinements.

Joseph E. Cavanaugh, Andrew A. Neath

Proceedings of the International Encyclopedia of Statistical Science, 2011

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

Bootstrap variants of the Akaike information criterion for mixed model selection.

Junfeng Shang, Joseph E. Cavanaugh

Comput. Stat. Data Anal., 2008

2006

An improved Akaike information criterion for state-space model selection.

Thomas Bengtsson, Joseph E. Cavanaugh

Comput. Stat. Data Anal., 2006

2004

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

1995

Optic Flow Field Segmentation and Motion Estimation Using a Robust Genetic Partitioning Algorithm.

Yan Huang, Kannappan Palaniappan, Xinhua Zhuang, Joseph E. Cavanaugh

IEEE Trans. Pattern Anal. Mach. Intell., 1995