NDLI: Measures of biomarker dependence using a copula-based multivariate epsilon–skew

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Measures of biomarker dependence using a copula-based multivariate epsilon–skew–normal family of distributions

Content Provider	Scilit
Author	Hutson, Alan D. Wilding, Gregory E. Mashtare, Terry L. Vexler, Albert
Copyright Year	2015
Description	Journal: Journal of Applied Statistics 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.
Related Links	http://europepmc.org/articles/pmc4763942?pdf=render https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4763942/pdf
Ending Page	2753
Page Count	20
Starting Page	2734
ISSN	02664763
e-ISSN	13600532
DOI	10.1080/02664763.2015.1049130
Journal	Journal of Applied Statistics
Issue Number	12
Volume Number	42
Language	English
Publisher	Informa UK Limited
Publisher Date	2015-05-12
Access Restriction	Open
Subject Keyword	Journal: Journal of Applied Statistics Mathematical Psychology Conditional Expectation Conditional Correlation Conditional Dependence
Content Type	Text
Subject	Statistics and Probability Statistics, Probability and Uncertainty

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