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Artigo de periodico
Zero-spiked regression models generated by gamma random variables with application in the resin oil production (2019)
Hashimoto, Elizabeth M; Ortega, Edwin Moises Marcos; Cordeiro, Gauss M; Cancho, Vicente Garibay ; Klauberg, Carine
Source: Journal of Statistical Computation and Simulation. Unidade: ESALQ
Subjects: REGRESSÃO LINEAR, ÓLEOS VEGETAIS, COPAÍBA, RESINAS VEGETAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HASHIMOTO, Elizabeth M et al. Zero-spiked regression models generated by gamma random variables with application in the resin oil production. Journal of Statistical Computation and Simulation, v. 89, n. 1, p. 52-70, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2018.1534116. Acesso em: 17 nov. 2024.
APA
Hashimoto, E. M., Ortega, E. M. M., Cordeiro, G. M., Cancho, V. G., & Klauberg, C. (2019). Zero-spiked regression models generated by gamma random variables with application in the resin oil production. Journal of Statistical Computation and Simulation, 89( 1), 52-70. doi:10.1080/00949655.2018.1534116
NLM
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Klauberg C. Zero-spiked regression models generated by gamma random variables with application in the resin oil production [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 1): 52-70.[citado 2024 nov. 17 ] Available from: https://doi.org/10.1080/00949655.2018.1534116
Vancouver
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Klauberg C. Zero-spiked regression models generated by gamma random variables with application in the resin oil production [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 1): 52-70.[citado 2024 nov. 17 ] Available from: https://doi.org/10.1080/00949655.2018.1534116
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
Source: Journal of Statistical Theory and Applications. Unidade: ESALQ
Subjects: 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: 17 nov. 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 nov. 17 ] 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 nov. 17 ] 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
Source: Journal of Statistical Theory and Applications. Unidade: ESALQ
Subjects: 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: 17 nov. 2024.
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 2024 nov. 17 ] 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 2024 nov. 17 ] Available from: https://doi.org/10.2991/jsta.2017.16.4.9
Artigo de periodico
New flexible regression models generated by gamma random variables with censored data (2016)
Hashimoto, Elizabeth M; Cordeiro, Gauss M; Ortega, Edwin Moises Marcos ; Hamedani, G. G
Source: International Journal of Statistics and Probability. Unidade: ESALQ
Subjects: DADOS CENSURADOS, DISTRIBUIÇÕES (PROBABILIDADE), MODELOS MATEMÁTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HASHIMOTO, Elizabeth M et al. New flexible regression models generated by gamma random variables with censored data. International Journal of Statistics and Probability, v. 5, n. 3, p. 9-31, 2016Tradução . . Disponível em: https://doi.org/10.5539/ijsp.v5n3p9. Acesso em: 17 nov. 2024.
APA
Hashimoto, E. M., Cordeiro, G. M., Ortega, E. M. M., & Hamedani, G. G. (2016). New flexible regression models generated by gamma random variables with censored data. International Journal of Statistics and Probability, 5( 3), 9-31. doi:10.5539/ijsp.v5n3p9
NLM
Hashimoto EM, Cordeiro GM, Ortega EMM, Hamedani GG. New flexible regression models generated by gamma random variables with censored data [Internet]. International Journal of Statistics and Probability. 2016 ; 5( 3): 9-31.[citado 2024 nov. 17 ] Available from: https://doi.org/10.5539/ijsp.v5n3p9
Vancouver
Hashimoto EM, Cordeiro GM, Ortega EMM, Hamedani GG. New flexible regression models generated by gamma random variables with censored data [Internet]. International Journal of Statistics and Probability. 2016 ; 5( 3): 9-31.[citado 2024 nov. 17 ] Available from: https://doi.org/10.5539/ijsp.v5n3p9

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