Analysis of Antibody Data Using Skew-normal and Skew-T Mixture Models
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 distr...
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| Format: | Article |
| Language: | English |
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Instituto Nacional de Estatística | Statistics Portugal
2024-02-01
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| Series: | Revstat Statistical Journal |
| Subjects: | |
| Online Access: | https://revstat.ine.pt/index.php/REVSTAT/article/view/455 |
| _version_ | 1797300155931688960 |
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| author | Tiago Dias Domingues Helena Mouriño Nuno Sepúlveda |
| author_facet | Tiago Dias Domingues Helena Mouriño Nuno Sepúlveda |
| author_sort | Tiago Dias Domingues |
| collection | DOAJ |
| description |
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.
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| first_indexed | 2024-03-07T23:02:10Z |
| format | Article |
| id | doaj.art-7074eafa1377410d97c84517497603b7 |
| institution | Directory Open Access Journal |
| issn | 1645-6726 2183-0371 |
| language | English |
| last_indexed | 2024-03-07T23:02:10Z |
| publishDate | 2024-02-01 |
| publisher | Instituto Nacional de Estatística | Statistics Portugal |
| record_format | Article |
| series | Revstat Statistical Journal |
| spelling | doaj.art-7074eafa1377410d97c84517497603b72024-02-22T12:22:52ZengInstituto Nacional de Estatística | Statistics PortugalRevstat Statistical Journal1645-67262183-03712024-02-0122110.57805/revstat.v22i1.455Analysis of Antibody Data Using Skew-normal and Skew-T Mixture ModelsTiago Dias Domingues 0Helena Mouriño1Nuno Sepúlveda2Universidade de LisboaUniversidade de LisboaUniversidade de Lisboa 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. https://revstat.ine.pt/index.php/REVSTAT/article/view/455Finite mixture modelsSkew-Normalskew-tseropositivity |
| spellingShingle | Tiago Dias Domingues Helena Mouriño Nuno Sepúlveda Analysis of Antibody Data Using Skew-normal and Skew-T Mixture Models Revstat Statistical Journal Finite mixture models Skew-Normal skew-t seropositivity |
| title | Analysis of Antibody Data Using Skew-normal and Skew-T Mixture Models |
| title_full | Analysis of Antibody Data Using Skew-normal and Skew-T Mixture Models |
| title_fullStr | Analysis of Antibody Data Using Skew-normal and Skew-T Mixture Models |
| title_full_unstemmed | Analysis of Antibody Data Using Skew-normal and Skew-T Mixture Models |
| title_short | Analysis of Antibody Data Using Skew-normal and Skew-T Mixture Models |
| title_sort | analysis of antibody data using skew normal and skew t mixture models |
| topic | Finite mixture models Skew-Normal skew-t seropositivity |
| url | https://revstat.ine.pt/index.php/REVSTAT/article/view/455 |
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