A. Neath

发表

Regression and time series model selection using variants of the schwarz information criterion

Joseph E. Cavanaugh, Andrew A. Neath, J. Cavanaugh, 1997 .

Generalizing the derivation of the schwarz information criterion

J. Cavanaugh, A. Neath, 1999 .

Bayesian multiple comparisons and model selection

J. Cavanaugh, A. Neath, Javier E. Flores, 2018 .

Testing Statistical Hypotheses (3rd ed.). E. L. Lehmann and Joseph P. Romano

A. Neath, 2006 .

The Bayesian information criterion: background, derivation, and applications

J. Cavanaugh, A. Neath, 2012 .

The Akaike information criterion: Background, derivation, properties, application, interpretation, and refinements

J. Cavanaugh, A. Neath, Andrew A. Neath, 2019, WIREs Computational Statistics.

How to be a better Bayesian

Francisco J. Samaniego, Andrew A. Neath, F. Samaniego, 1996 .

Reconceptualizing the p-value from a likelihood ratio test: a probabilistic pairwise comparison of models based on Kullback-Leibler discrepancy measures

J. Cavanaugh, A. Neath, B. Riedle, 2020, Journal of applied statistics.

A regression model selection criterion based on bootstrap bumping for use with resistant fitting

J. Cavanaugh, A. Neath, 2000 .

On the total time on test transform of an IFRA distribution

F. Samaniego, A. Neath, 1992 .

BAYESIAN ESTIMATION OF LINEAR STATISTICAL MODEL BIAS

J. Cavanaugh, A. Neath, 2006 .

Model evaluation, discrepancy function estimation, and social choice theory

Adam G. Weyhaupt, J. Cavanaugh, A. Neath, 2014, Computational Statistics.

Linear Model Evaluation Based on Estimation of Model Bias

J. Cavanaugh, A. Neath, 2010 .

On the Efficacy of Bayesian Inference for Nonidentifiable Models

Francisco J. Samaniego, Andrew A. Neath, F. Samaniego, 1997 .

A Bayesian Approach to the Multiple Comparisons Problem

Joseph E. Cavanaugh, Andrew A. Neath, J. Cavanaugh, 2006, Journal of Data Science.

Book Reviews

F. Samaniego, F. Lorenz, R. Lomax, 2011 .

Polya tree distributions for statistical modeling of censored data

Andrew A. Neath, A. Neath, 2003, Adv. Decis. Sci..

An alternate version of the conceptual predictive statistic based on a symmetrized discrepancy measure

J. Cavanaugh, A. Neath, Simon L. Davies, 2010 .

Bayesian Estimation of Prediction Error and Variable Selection in Linear Regression

J. Cavanaugh, A. Neath, 2010 .

Model evaluation, discrepancy function estimation, and social choice theory

Joseph E. Cavanaugh, Andrew A. Neath, Adam G. Weyhaupt, 2015, Computational statistics (Zeitschrift).

Discrepancy-Based Model Selection Criteria Using Cross-Validation

J. Cavanaugh, A. Neath, Simon L. Davies, 2008 .

Estimation Optimality of Corrected AIC and Modified Cp in Linear Regression

Joseph E. Cavanaugh, Andrew A. Neath, J. Cavanaugh, 2006 .

Symptom Clusters in Women With Relapsing-Remitting Multiple Sclerosis

A. Neath, P. Newland, M. Riley, 2012, The Journal of neuroscience nursing : journal of the American Association of Neuroscience Nurses.

Multiple Comparisons Testing from a Bayesian Perspective

Joseph E. Cavanaugh, Andrew A. Neath, J. Cavanaugh, 2011, International Encyclopedia of Statistical Science.

Performance of Variable Selection Methods in Regression Using Variations of the Bayesian Information Criterion

Tom Burr, Joseph E. Cavanaugh, Herb Fry, 2008, Commun. Stat. Simul. Comput..

Cross validation model selection criteria for linear regression based on the Kullback–Leibler discrepancy

Joseph E. Cavanaugh, Andrew A. Neath, J. Cavanaugh, 2005 .

A bootstrap method for assessing uncertainty in Kullback-Leibler discrepancy model selection problems

J. Cavanaugh, A. Neath, Benjamim Riedle, 2012 .

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

Joseph E. Cavanaugh, Andrew A. Neath, J. Cavanaugh, 2011, International Encyclopedia of Statistical Science.