The Log-gamma-logistic regression model: estimation, sensibility and residual analysis (2017)
- Authors:
- Autor USP: ORTEGA, EDWIN MOISES MARCOS - ESALQ
- Unidade: ESALQ
- Subjects: DADOS CENSURADOS; DISTRIBUIÇÃO LOGÍSTICA; MODELOS MATEMÁTICOS
- Keywords: Análise residual; Modelo de regressão
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Journal of Statistical Theory and Applications
- ISSN: 1538-7887
- Volume/Número/Paginação/Ano: v. 16, n. 4, p. 547-564, 2017
-
ABNT
HASHIMOTO, Elizabeth M et al. The Log-gamma-logistic regression model: estimation, sensibility and residual analysis. Journal of Statistical Theory and Applications, v. 16, n. 4, p. 547-564, 2017Tradução . . Disponível em: https://www.atlantis-press.com/journals/jsta/25887941. Acesso em: 27 set. 2024. -
APA
Hashimoto, E. M., Edwin Moises Marcos Ortega,, Cordeiro, G. M., & Hamedani, G. G. (2017). The Log-gamma-logistic regression model: estimation, sensibility and residual analysis. Journal of Statistical Theory and Applications, 16( 4), 547-564. Recuperado de https://www.atlantis-press.com/journals/jsta/25887941 -
NLM
Hashimoto EM, Edwin Moises Marcos Ortega, Cordeiro GM, Hamedani GG. The Log-gamma-logistic regression model: estimation, sensibility and residual analysis [Internet]. Journal of Statistical Theory and Applications. 2017 ; 16( 4): 547-564.[citado 2024 set. 27 ] Available from: https://www.atlantis-press.com/journals/jsta/25887941 -
Vancouver
Hashimoto EM, Edwin Moises Marcos Ortega, Cordeiro GM, Hamedani GG. The Log-gamma-logistic regression model: estimation, sensibility and residual analysis [Internet]. Journal of Statistical Theory and Applications. 2017 ; 16( 4): 547-564.[citado 2024 set. 27 ] Available from: https://www.atlantis-press.com/journals/jsta/25887941 - The extended weibull geometric family
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