NetDA: An R Package for Network-Based Discriminant Analysis Subject to Multilabel Classes
In this paper, we introduce the R package NetDA, which aims to deal with multiclassification with network structures in predictors accommodated. To address the natural feature of network structures, we apply Gaussian graphical models to characterize dependence structures of the predictors and direct...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Probability and Statistics |
| Online Access: | http://dx.doi.org/10.1155/2022/1041752 |
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| _version_ | 1849304275730038784 |
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| author | Li-Pang Chen |
| author_facet | Li-Pang Chen |
| author_sort | Li-Pang Chen |
| collection | DOAJ |
| description | In this paper, we introduce the R package NetDA, which aims to deal with multiclassification with network structures in predictors accommodated. To address the natural feature of network structures, we apply Gaussian graphical models to characterize dependence structures of the predictors and directly estimate the precision matrix. After that, the estimated precision matrix is employed to linear discriminant functions and quadratic discriminant functions. The R package NetDA is now available on CRAN, and the demonstration of functions is summarized as a vignette in the online documentation. |
| format | Article |
| id | doaj-art-198c6cd0761c4f59ad78f61151d2f7b2 |
| institution | Kabale University |
| issn | 1687-9538 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Probability and Statistics |
| spelling | doaj-art-198c6cd0761c4f59ad78f61151d2f7b22025-08-20T03:55:48ZengWileyJournal of Probability and Statistics1687-95382022-01-01202210.1155/2022/1041752NetDA: An R Package for Network-Based Discriminant Analysis Subject to Multilabel ClassesLi-Pang Chen0Department of StatisticsIn this paper, we introduce the R package NetDA, which aims to deal with multiclassification with network structures in predictors accommodated. To address the natural feature of network structures, we apply Gaussian graphical models to characterize dependence structures of the predictors and directly estimate the precision matrix. After that, the estimated precision matrix is employed to linear discriminant functions and quadratic discriminant functions. The R package NetDA is now available on CRAN, and the demonstration of functions is summarized as a vignette in the online documentation.http://dx.doi.org/10.1155/2022/1041752 |
| spellingShingle | Li-Pang Chen NetDA: An R Package for Network-Based Discriminant Analysis Subject to Multilabel Classes Journal of Probability and Statistics |
| title | NetDA: An R Package for Network-Based Discriminant Analysis Subject to Multilabel Classes |
| title_full | NetDA: An R Package for Network-Based Discriminant Analysis Subject to Multilabel Classes |
| title_fullStr | NetDA: An R Package for Network-Based Discriminant Analysis Subject to Multilabel Classes |
| title_full_unstemmed | NetDA: An R Package for Network-Based Discriminant Analysis Subject to Multilabel Classes |
| title_short | NetDA: An R Package for Network-Based Discriminant Analysis Subject to Multilabel Classes |
| title_sort | netda an r package for network based discriminant analysis subject to multilabel classes |
| url | http://dx.doi.org/10.1155/2022/1041752 |
| work_keys_str_mv | AT lipangchen netdaanrpackagefornetworkbaseddiscriminantanalysissubjecttomultilabelclasses |