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Artigo de periodico
The new family of distributions and applications in heteroscedastic regression analysis (2017)
Cordeiro, Gauss M; Ramires, Thiago G; Ortega, Edwin Moises Marcos; Alizadeh, Morad
Fonte: Journal of Statistical Theory and Applications. Unidade: ESALQ
Assuntos: ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, DADOS CENSURADOS, DISTRIBUIÇÕES (PROBABILIDADE), HETEROSCEDASTICIDADE, MÉTODO DE CAUCHY, VEROSSIMILHANÇA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CORDEIRO, Gauss M et al. The new family of distributions and applications in heteroscedastic regression analysis. Journal of Statistical Theory and Applications, v. 16, n. 3, p. 401-418, 2017Tradução . . Disponível em: https://doi.org/10.2991/jsta.2017.16.3.11. Acesso em: 13 nov. 2025.
APA
Cordeiro, G. M., Ramires, T. G., Ortega, E. M. M., & Alizadeh, M. (2017). The new family of distributions and applications in heteroscedastic regression analysis. Journal of Statistical Theory and Applications, 16( 3), 401-418. doi:10.2991/jsta.2017.16.3.11
NLM
Cordeiro GM, Ramires TG, Ortega EMM, Alizadeh M. The new family of distributions and applications in heteroscedastic regression analysis [Internet]. Journal of Statistical Theory and Applications. 2017 ; 16( 3): 401-418.[citado 2025 nov. 13 ] Available from: https://doi.org/10.2991/jsta.2017.16.3.11
Vancouver
Cordeiro GM, Ramires TG, Ortega EMM, Alizadeh M. The new family of distributions and applications in heteroscedastic regression analysis [Internet]. Journal of Statistical Theory and Applications. 2017 ; 16( 3): 401-418.[citado 2025 nov. 13 ] Available from: https://doi.org/10.2991/jsta.2017.16.3.11
Artigo de periodico
The Log-gamma-logistic regression model: estimation, sensibility and residual analysis (2017)
Hashimoto, Elizabeth M; Edwin Moises Marcos Ortega ; Cordeiro, Gauss M; Hamedani, G. G
Fonte: Journal of Statistical Theory and Applications. Unidade: ESALQ
Assuntos: DADOS CENSURADOS, DISTRIBUIÇÃO LOGÍSTICA, MODELOS MATEMÁTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 13 nov. 2025.
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 2025 nov. 13 ] 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 2025 nov. 13 ] Available from: https://www.atlantis-press.com/journals/jsta/25887941
Artigo de periodico
The Log-gamma-logistic regression model: estimation, sensibility and residual analysis (2017)
Hashimoto, Elizabeth M; Ortega, Edwin Moises Marcos ; Cordeiro, Gauss M; Hamedani, G.G
Fonte: Journal of Statistical Theory and Applications. Unidade: ESALQ
Assuntos: DADOS CENSURADOS, DISTRIBUIÇÃO LOGÍSTICA, MODELOS MATEMÁTICOS, VEROSSIMILHANÇA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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://doi.org/10.2991/jsta.2017.16.4.9. Acesso em: 13 nov. 2025.
APA
Hashimoto, E. M., Ortega, E. M. M., 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. doi:10.2991/jsta.2017.16.4.9
NLM
Hashimoto EM, Ortega EMM, 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 2025 nov. 13 ] Available from: https://doi.org/10.2991/jsta.2017.16.4.9
Vancouver
Hashimoto EM, Ortega EMM, 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 2025 nov. 13 ] Available from: https://doi.org/10.2991/jsta.2017.16.4.9

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