Application of spatial auto-beta models in statistical classification
In this paper, spatial data specified by auto-beta models is analysed by considering a supervised classification problem of classifying feature observation into one of two populations. Two classification rules based on conditional Bayes discriminant function (BDF) and linear discriminant function (L...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Vilnius University Press
2021-12-01
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| Series: | Lietuvos Matematikos Rinkinys |
| Subjects: | |
| Online Access: | https://www.zurnalai.vu.lt/LMR/article/view/25219 |
| Summary: | In this paper, spatial data specified by auto-beta models is analysed by considering a supervised classification problem of classifying feature observation into one of two populations. Two classification rules based on conditional Bayes discriminant function (BDF) and linear discriminant function (LDF) are proposed. These classification rules are critically compared by the values of the actual error rates through the simulation study. |
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| ISSN: | 0132-2818 2335-898X |