Forthcoming

Analysis of Antibody Data Using Skew-normal and Skew-T Mixture Models

Accepted - March 2022

Authors

Keywords:

Finite mixture models, Skew-Normal, skew-t, seropositivity

Abstract

Gaussian mixture models, which assume a Normal distribution for each component, are popular in antibody (or serological) data analysis to help determining antibody-positive and antibody-negative individuals. In this work, we advocate using finite mixture models based on Skew-Normal and Skew-t distributions for serological data analysis. These flexible mixing distributions have the advantage of describing right and left asymmetry often observed in the distributions of known antibody-negative and antibody-positive individuals, respectively. We illustrate the application of these alternative mixture models in a data set on the role of human herpesviruses in the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Additional Files

Published

2022-03-30

How to Cite

Dias Domingues , T., Mouriño, H., & Sepúlveda, N. (2022). Analysis of Antibody Data Using Skew-normal and Skew-T Mixture Models: Accepted - March 2022. REVSTAT-Statistical Journal. Retrieved from https://revstat.ine.pt/index.php/REVSTAT/article/view/455

Issue

Section

Forthcoming Paper