Joseph E. Cavanaugh

19 papers Journal 17
YearRankTypeTitle / Venue / Authors
2025 J jnl
A new class of information criteria for improved prediction in the presence of training/validation data heterogeneity.
Comput. Stat.
Javier E. Flores, Joseph E. Cavanaugh, Andrew A. Neath
2024 J jnl
Assessing Variable Importance for Best Subset Selection.
Entropy
Jacob Seedorff, Joseph E. Cavanaugh
2024 J jnl
Bootstrap Approximation of Model Selection Probabilities for Multimodel Inference Frameworks.
Entropy
Andres Dajles, Joseph E. Cavanaugh
2024 J jnl
Can a Transparent Machine Learning Algorithm Predict Better than Its Black Box Counterparts? A Benchmarking Study Using 110 Data Sets.
Entropy
Ryan A. Peterson, Max McGrath, Joseph E. Cavanaugh
2023 J jnl
A comprehensive framework to estimate the frequency, duration, and risk factors for diagnostic delays using bootstrapping-based simulation methods.
BMC Medical Informatics Decis. Mak.
Aaron C. Miller, Joseph E. Cavanaugh, Alan T. Arakkal, Scott H. Koeneman, Philip M. Polgreen
2022 J jnl
Agglomerative and divisive hierarchical Bayesian clustering.
Comput. Stat. Data Anal.
Elliot Burghardt, Daniel K. Sewell, Joseph E. Cavanaugh
2022 J jnl
Probabilistic Pairwise Model Comparisons Based on Bootstrap Estimators of the Kullback-Leibler Discrepancy.
Entropy
Andres Dajles, Joseph E. Cavanaugh
2018 J jnl
Extending AIC to best subset regression.
Comput. Stat.
J. G. Liao, Joseph E. Cavanaugh, Timothy L. McMurry
2018 J jnl
Forensics: Assessing model goodness: A machine learning view.
Encycl. Semantic Comput. Robotic Intell.
Joseph R. Barr, Joseph E. Cavanaugh
2018 J jnl
Model selection criteria based on cross-validatory concordance statistics.
Comput. Stat.
Patrick Ten Eyck, Joseph E. Cavanaugh
2016 J jnl
A multistage algorithm for best-subset model selection based on the Kullback-Leibler discrepancy.
Comput. Stat.
Tao Zhang, Joseph E. Cavanaugh
2015 J jnl
Model evaluation, discrepancy function estimation, and social choice theory.
Comput. Stat.
Andrew A. Neath, Joseph E. Cavanaugh, Adam G. Weyhaupt
2011 — ch.
Akaike's Information Criterion: Background, Derivation, Properties, and Refinements.
International Encyclopedia of Statistical Science
Joseph E. Cavanaugh, Andrew A. Neath
2011 — ch.
Multiple Comparisons Testing from a Bayesian Perspective.
International Encyclopedia of Statistical Science
Andrew A. Neath, Joseph E. Cavanaugh
2008 J jnl
Bootstrap variants of the Akaike information criterion for mixed model selection.
Comput. Stat. Data Anal.
Junfeng Shang, Joseph E. Cavanaugh
2008 J jnl
Performance of Variable Selection Methods in Regression Using Variations of the Bayesian Information Criterion.
Commun. Stat. Simul. Comput.
Tom Burr, Herb Fry, Brian McVey, Eric Sander, Joseph E. Cavanaugh, Andrew A. Neath
2006 J jnl
An improved Akaike information criterion for state-space model selection.
Comput. Stat. Data Anal.
Thomas Bengtsson, Joseph E. Cavanaugh
2004 J jnl
An autoregressive model for analysis of ice sheet elevation change time series.
IEEE Trans. Geosci. Remote. Sens.
Adam C. Ferguson, Curt H. Davis, Joseph E. Cavanaugh
1995 J jnl
Optic Flow Field Segmentation and Motion Estimation Using a Robust Genetic Partitioning Algorithm.
IEEE Trans. Pattern Anal. Mach. Intell.
Yan Huang, Kannappan Palaniappan, Xinhua Zhuang, Joseph E. Cavanaugh