An alternative promotion time cure model with overdispersed number of competing causes: an application to melanoma data (2021)
- Authors:
- Autor USP: ANDRADE FILHO, MÁRIO DE CASTRO - ICMC
- Unidade: ICMC
- DOI: 10.3390/math9151815
- Subjects: ANÁLISE DE SOBREVIVÊNCIA; ALGORITMOS; PROBABILIDADE APLICADA
- Keywords: bell distribution; EM algorithm; model comparison; maximum likelihood
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Mathematics
- ISSN: 2227-7390
- Volume/Número/Paginação/Ano: v. 9, n. 15, p. 1-14, 2021
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
ABNT
GALLARDO, Diego I. e CASTRO, Mário de e GÓMEZ, Héctor W. An alternative promotion time cure model with overdispersed number of competing causes: an application to melanoma data. Mathematics, v. 9, n. 15, p. 1-14, 2021Tradução . . Disponível em: https://doi.org/10.3390/math9151815. Acesso em: 27 dez. 2025. -
APA
Gallardo, D. I., Castro, M. de, & Gómez, H. W. (2021). An alternative promotion time cure model with overdispersed number of competing causes: an application to melanoma data. Mathematics, 9( 15), 1-14. doi:10.3390/math9151815 -
NLM
Gallardo DI, Castro M de, Gómez HW. An alternative promotion time cure model with overdispersed number of competing causes: an application to melanoma data [Internet]. Mathematics. 2021 ; 9( 15): 1-14.[citado 2025 dez. 27 ] Available from: https://doi.org/10.3390/math9151815 -
Vancouver
Gallardo DI, Castro M de, Gómez HW. An alternative promotion time cure model with overdispersed number of competing causes: an application to melanoma data [Internet]. Mathematics. 2021 ; 9( 15): 1-14.[citado 2025 dez. 27 ] Available from: https://doi.org/10.3390/math9151815 - Influence assessment in an heteroscedastic errors-in-variables model
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- Maximum penalized likelihood inference in classical errors-in-variables model
- New estimation methods for the Grubbs model
Informações sobre o DOI: 10.3390/math9151815 (Fonte: oaDOI API)
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