Composite likelihood inference for analysis of individual animal identification data
Individual identification data collection is a common practice in animal behaviour, movement ecology, and conservation biology. While likelihood analysis is widely employed for ecological insights, the complexity of individual identification data, characterized by numerous interdependent individuals...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-12-01
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| Series: | Ecological Informatics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1574954125003073 |
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| author | Xueli Xu Xiaoyue Zhang Hal Whitehead Dehan Kong Ximing Xu |
| author_facet | Xueli Xu Xiaoyue Zhang Hal Whitehead Dehan Kong Ximing Xu |
| author_sort | Xueli Xu |
| collection | DOAJ |
| description | Individual identification data collection is a common practice in animal behaviour, movement ecology, and conservation biology. While likelihood analysis is widely employed for ecological insights, the complexity of individual identification data, characterized by numerous interdependent individuals and identification times, makes direct likelihood calculation challenging. To address this, we introduce a composite likelihood inference framework. We establish the consistency and asymptotic normality of maximum composite likelihood estimators within this framework. Furthermore, we develop a composite likelihood-based information criterion for model selection, capable of handling complex individual identification data. Our approach is demonstrated through extensive simulations and applied to the northern bottlenose whale population in the Gully, Nova Scotia. This study provides a statistically rigorous framework for individual animal identification models, with potential applications extending beyond whale populations. |
| format | Article |
| id | doaj-art-90982e564ea34616a5bf3cebbf0aee4f |
| institution | Kabale University |
| issn | 1574-9541 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Informatics |
| spelling | doaj-art-90982e564ea34616a5bf3cebbf0aee4f2025-08-20T05:05:38ZengElsevierEcological Informatics1574-95412025-12-019010329810.1016/j.ecoinf.2025.103298Composite likelihood inference for analysis of individual animal identification dataXueli Xu0Xiaoyue Zhang1Hal Whitehead2Dehan Kong3Ximing Xu4Center for Biomedical Digital Science, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, ChinaDepartment of Biostatistics, Harvard University, Chan School of Public Health, Boston, MA, United StatesDepartment of Biology, Dalhousie University, Halifax, Nova Scotia, CanadaDepartment of Statistical Sciences, University of Toronto, Ontario M5S 3G3, CanadaBig Data Center for Children's Medical Care, Children's Hospital of Chongqing Medical University; National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, 400014, China; Corresponding author.Individual identification data collection is a common practice in animal behaviour, movement ecology, and conservation biology. While likelihood analysis is widely employed for ecological insights, the complexity of individual identification data, characterized by numerous interdependent individuals and identification times, makes direct likelihood calculation challenging. To address this, we introduce a composite likelihood inference framework. We establish the consistency and asymptotic normality of maximum composite likelihood estimators within this framework. Furthermore, we develop a composite likelihood-based information criterion for model selection, capable of handling complex individual identification data. Our approach is demonstrated through extensive simulations and applied to the northern bottlenose whale population in the Gully, Nova Scotia. This study provides a statistically rigorous framework for individual animal identification models, with potential applications extending beyond whale populations.http://www.sciencedirect.com/science/article/pii/S1574954125003073Individual identification dataComposite likelihoodModel selectionAnimal movementAnimal social structure |
| spellingShingle | Xueli Xu Xiaoyue Zhang Hal Whitehead Dehan Kong Ximing Xu Composite likelihood inference for analysis of individual animal identification data Ecological Informatics Individual identification data Composite likelihood Model selection Animal movement Animal social structure |
| title | Composite likelihood inference for analysis of individual animal identification data |
| title_full | Composite likelihood inference for analysis of individual animal identification data |
| title_fullStr | Composite likelihood inference for analysis of individual animal identification data |
| title_full_unstemmed | Composite likelihood inference for analysis of individual animal identification data |
| title_short | Composite likelihood inference for analysis of individual animal identification data |
| title_sort | composite likelihood inference for analysis of individual animal identification data |
| topic | Individual identification data Composite likelihood Model selection Animal movement Animal social structure |
| url | http://www.sciencedirect.com/science/article/pii/S1574954125003073 |
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