Modeling the spatial patterns of antenatal care utilization in Nigeria with inference based on Pólya-Gamma mixtures (2024)
- Authors:
- Autor USP: EGBON, OSAFU AUGUSTINE - INTER: ICMC -UFSCAR
- Unidade: INTER: ICMC -UFSCAR
- DOI: 10.1080/02664763.2022.2164561
- Subjects: INFERÊNCIA BAYESIANA; REGRESSÃO LINEAR; ESTATÍSTICA APLICADA; FATORES SOCIOECONÔMICOS; DIAGNÓSTICO PRÉ-NATAL
- Keywords: Antenatal care; zero-inflated; negative binomial; Pólya-Gamma; data-augmentation; Bayesian spatial model
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Journal of Applied Statistics
- ISSN: 0266-4763
- Volume/Número/Paginação/Ano: v. 51, n. 5, p. 866-890, 2024
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
-
ABNT
EGBON, Osafu Augustine e GAYAWAN, Ezra. Modeling the spatial patterns of antenatal care utilization in Nigeria with inference based on Pólya-Gamma mixtures. Journal of Applied Statistics, v. 51, n. 5, p. 866-890, 2024Tradução . . Disponível em: https://doi.org/10.1080/02664763.2022.2164561. Acesso em: 03 maio 2024. -
APA
Egbon, O. A., & Gayawan, E. (2024). Modeling the spatial patterns of antenatal care utilization in Nigeria with inference based on Pólya-Gamma mixtures. Journal of Applied Statistics, 51( 5), 866-890. doi:10.1080/02664763.2022.2164561 -
NLM
Egbon OA, Gayawan E. Modeling the spatial patterns of antenatal care utilization in Nigeria with inference based on Pólya-Gamma mixtures [Internet]. Journal of Applied Statistics. 2024 ; 51( 5): 866-890.[citado 2024 maio 03 ] Available from: https://doi.org/10.1080/02664763.2022.2164561 -
Vancouver
Egbon OA, Gayawan E. Modeling the spatial patterns of antenatal care utilization in Nigeria with inference based on Pólya-Gamma mixtures [Internet]. Journal of Applied Statistics. 2024 ; 51( 5): 866-890.[citado 2024 maio 03 ] Available from: https://doi.org/10.1080/02664763.2022.2164561 - Bayesian Spatial Process Models for Activation Patterns in Transcranial Magnetic Stimulation Mapping
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Informações sobre o DOI: 10.1080/02664763.2022.2164561 (Fonte: oaDOI API)
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