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Updated: Mar 25, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Measures of biomarker dependence using a copula-based multivariate epsilon-skew-normal family of distributions
Alan D Hutson1, Gregory E Wilding1, Terry L Mashtare1
1Department of Biostatistics, University at Buffalo, 706 Kimball Tower, 3435 Main St., Buffalo, NY 14214-3000, USA.
Abstract:
In this note we develop a new multivariate copula model based on epsilon-skew-normal marginal densities for the purpose of examining biomarker dependency structures. We illustrate the flexibility and utility of this model via a variety of graphical tools and a data analysis example pertaining to salivary biomarker. The multivariate normal model is a sub-model of the multivariate epsilon-skew-normal distribution.
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