A new class of cure rate survival models: properties, inference and applications (2021)
- Authors:
- USP affiliated authors: SUZUKI, ADRIANO KAMIMURA - ICMC ; CANCHO, VICENTE GARIBAY - ICMC ; LOUZADA NETO, FRANCISCO - ICMC
- Unidade: ICMC
- DOI: 10.1142/S2424922X21500017
- Subjects: ANÁLISE DE SOBREVIVÊNCIA; ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO; CURA
- Keywords: Cured fraction; Likelihood function; Scoring credit; Cure rate models
- Language: Inglês
- Imprenta:
- Source:
- Título: Advances in Data Science and Adaptive Analysis
- ISSN: 2424-922X
- Volume/Número/Paginação/Ano: v. 13, n. 1, p. 2150001-1-2150001-15, 2021
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
BARRIGA, Gladys Dorotea Cacsire et al. A new class of cure rate survival models: properties, inference and applications. Advances in Data Science and Adaptive Analysis, v. 13, n. 1, p. 2150001-1-2150001-15, 2021Tradução . . Disponível em: https://doi.org/10.1142/S2424922X21500017. Acesso em: 02 out. 2024. -
APA
Barriga, G. D. C., Suzuki, A. K., Cancho, V. G., & Louzada, F. (2021). A new class of cure rate survival models: properties, inference and applications. Advances in Data Science and Adaptive Analysis, 13( 1), 2150001-1-2150001-15. doi:10.1142/S2424922X21500017 -
NLM
Barriga GDC, Suzuki AK, Cancho VG, Louzada F. A new class of cure rate survival models: properties, inference and applications [Internet]. Advances in Data Science and Adaptive Analysis. 2021 ; 13( 1): 2150001-1-2150001-15.[citado 2024 out. 02 ] Available from: https://doi.org/10.1142/S2424922X21500017 -
Vancouver
Barriga GDC, Suzuki AK, Cancho VG, Louzada F. A new class of cure rate survival models: properties, inference and applications [Internet]. Advances in Data Science and Adaptive Analysis. 2021 ; 13( 1): 2150001-1-2150001-15.[citado 2024 out. 02 ] Available from: https://doi.org/10.1142/S2424922X21500017 - On estimation and influence diagnostics for a bivariate promotion lifetime model based on the FGM Copula: a fully bayesian computation
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Informações sobre o DOI: 10.1142/S2424922X21500017 (Fonte: oaDOI API)
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