Spatial modelling of the joint burden of malaria and anaemia co-morbidity in children: a bayesian geoadditive perspective (2022)
- Authors:
- Autor USP: EGBON, OSAFU AUGUSTINE - INTER: ICMC -UFSCAR
- Unidade: INTER: ICMC -UFSCAR
- DOI: 10.1080/23737484.2022.2031345
- Subjects: INFERÊNCIA BAYESIANA; PROCESSOS GAUSSIANOS; MALÁRIA; ANEMIA; CRIANÇAS
- Keywords: latent Gaussian model
- Language: Inglês
- Imprenta:
- Publisher place: Philadelphia
- Date published: 2022
- Source:
- Título do periódico: Communications in Statistics : case studies, data analysis and applications
- ISSN: 2373-7484
- Volume/Número/Paginação/Ano: v. 8, n. 2, p. 264-281, 2022
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
GAYAWAN, Ezra e EGBON, Osafu Augustine e ADEBAYO, Samson B. Spatial modelling of the joint burden of malaria and anaemia co-morbidity in children: a bayesian geoadditive perspective. Communications in Statistics : case studies, data analysis and applications, v. 8, n. 2, p. 264-281, 2022Tradução . . Disponível em: https://doi.org/10.1080/23737484.2022.2031345. Acesso em: 29 maio 2024. -
APA
Gayawan, E., Egbon, O. A., & Adebayo, S. B. (2022). Spatial modelling of the joint burden of malaria and anaemia co-morbidity in children: a bayesian geoadditive perspective. Communications in Statistics : case studies, data analysis and applications, 8( 2), 264-281. doi:10.1080/23737484.2022.2031345 -
NLM
Gayawan E, Egbon OA, Adebayo SB. Spatial modelling of the joint burden of malaria and anaemia co-morbidity in children: a bayesian geoadditive perspective [Internet]. Communications in Statistics : case studies, data analysis and applications. 2022 ; 8( 2): 264-281.[citado 2024 maio 29 ] Available from: https://doi.org/10.1080/23737484.2022.2031345 -
Vancouver
Gayawan E, Egbon OA, Adebayo SB. Spatial modelling of the joint burden of malaria and anaemia co-morbidity in children: a bayesian geoadditive perspective [Internet]. Communications in Statistics : case studies, data analysis and applications. 2022 ; 8( 2): 264-281.[citado 2024 maio 29 ] Available from: https://doi.org/10.1080/23737484.2022.2031345 - Bayesian Spatial Process Models for Activation Patterns in Transcranial Magnetic Stimulation Mapping
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Informações sobre o DOI: 10.1080/23737484.2022.2031345 (Fonte: oaDOI API)
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