A New lifetime model for multivariate survival data with a surviving fraction (2016)
- Authors:
- USP affiliated authors: CANCHO, VICENTE GARIBAY - ICMC ; LOUZADA NETO, FRANCISCO - ICMC
- Unidade: ICMC
- DOI: 10.1080/00949655.2015.1007983
- Subjects: ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO; ESTATÍSTICA; ESTATÍSTICA APLICADA; INFERÊNCIA ESTATÍSTICA; INFERÊNCIA BAYESIANA; REGRESSÃO LINEAR; INFERÊNCIA PARAMÉTRICA; PROBABILIDADE
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Journal of Statistical Computation and Simulation
- ISSN: 0094-9655
- Volume/Número/Paginação/Ano: v. 86, n. 2, p. 279-292, 2016
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
- Licença: other-oa
-
ABNT
CANCHO, Vicente Garibay et al. A New lifetime model for multivariate survival data with a surviving fraction. Journal of Statistical Computation and Simulation, v. 86, n. 2, p. 279-292, 2016Tradução . . Disponível em: https://doi.org/10.1080/00949655.2015.1007983. Acesso em: 24 abr. 2024. -
APA
Cancho, V. G., Louzada, F., Dey, D. K., & Barriga, G. D. C. (2016). A New lifetime model for multivariate survival data with a surviving fraction. Journal of Statistical Computation and Simulation, 86( 2), 279-292. doi:10.1080/00949655.2015.1007983 -
NLM
Cancho VG, Louzada F, Dey DK, Barriga GDC. A New lifetime model for multivariate survival data with a surviving fraction [Internet]. Journal of Statistical Computation and Simulation. 2016 ; 86( 2): 279-292.[citado 2024 abr. 24 ] Available from: https://doi.org/10.1080/00949655.2015.1007983 -
Vancouver
Cancho VG, Louzada F, Dey DK, Barriga GDC. A New lifetime model for multivariate survival data with a surviving fraction [Internet]. Journal of Statistical Computation and Simulation. 2016 ; 86( 2): 279-292.[citado 2024 abr. 24 ] Available from: https://doi.org/10.1080/00949655.2015.1007983 - The Poisson-exponential model for recurrent event data: an application to bowel motility data
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Informações sobre o DOI: 10.1080/00949655.2015.1007983 (Fonte: oaDOI API)
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