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Artigo de periodico
Analysis of judiciary expenditure and productivity using machine learning techniques (2023)
Vasconcelos, Fernando Freire ; Sátiro, Renato Máximo ; Fávero, Luiz Paulo Lopes ; Bortoloto, Gabriela Troyano ; Corrêa, Hamilton Luiz
Fonte: Mathematics. Unidades: FEA, ESALQ
Assuntos: APRENDIZADO COMPUTACIONAL, DESPESAS PROCESSUAIS, PRODUTIVIDADE, REDES NEURAIS, SISTEMA JUDICIÁRIO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
VASCONCELOS, Fernando Freire et al. Analysis of judiciary expenditure and productivity using machine learning techniques. Mathematics, v. 11, p. 1-19, 2023Tradução . . Disponível em: https://doi.org/10.3390/math11143195. Acesso em: 06 jul. 2024.
APA
Vasconcelos, F. F., Sátiro, R. M., Fávero, L. P. L., Bortoloto, G. T., & Corrêa, H. L. (2023). Analysis of judiciary expenditure and productivity using machine learning techniques. Mathematics, 11, 1-19. doi:10.3390/math11143195
NLM
Vasconcelos FF, Sátiro RM, Fávero LPL, Bortoloto GT, Corrêa HL. Analysis of judiciary expenditure and productivity using machine learning techniques [Internet]. Mathematics. 2023 ; 11 1-19.[citado 2024 jul. 06 ] Available from: https://doi.org/10.3390/math11143195
Vancouver
Vasconcelos FF, Sátiro RM, Fávero LPL, Bortoloto GT, Corrêa HL. Analysis of judiciary expenditure and productivity using machine learning techniques [Internet]. Mathematics. 2023 ; 11 1-19.[citado 2024 jul. 06 ] Available from: https://doi.org/10.3390/math11143195
Artigo de periodico
Multilevel evidence on how policymakers may reduce avoidable deaths due to COVID-19: the case of Brazil (2022)
Souza, Rafael de Freitas ; Fávero, Luiz Paulo Lopes ; Haddad, Michel Ferreira Cardia; Corrêa, Hamilton Luiz
Fonte: International Journal of Mathematics in Operational Research. Unidades: FEARP, FEA
Assuntos: MODELAGEM DE DADOS, COVID-19, PAÍSES EM DESENVOLVIMENTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA, Rafael de Freitas et al. Multilevel evidence on how policymakers may reduce avoidable deaths due to COVID-19: the case of Brazil. International Journal of Mathematics in Operational Research, v. 21, n. 3, p. 321-337, 2022Tradução . . Acesso em: 06 jul. 2024.
APA
Souza, R. de F., Fávero, L. P. L., Haddad, M. F. C., & Corrêa, H. L. (2022). Multilevel evidence on how policymakers may reduce avoidable deaths due to COVID-19: the case of Brazil. International Journal of Mathematics in Operational Research, 21( 3), 321-337. doi:10.1504/IJMOR.2022.122218
NLM
Souza R de F, Fávero LPL, Haddad MFC, Corrêa HL. Multilevel evidence on how policymakers may reduce avoidable deaths due to COVID-19: the case of Brazil. International Journal of Mathematics in Operational Research. 2022 ; 21( 3): 321-337.[citado 2024 jul. 06 ]
Vancouver
Souza R de F, Fávero LPL, Haddad MFC, Corrêa HL. Multilevel evidence on how policymakers may reduce avoidable deaths due to COVID-19: the case of Brazil. International Journal of Mathematics in Operational Research. 2022 ; 21( 3): 321-337.[citado 2024 jul. 06 ]
Artigo de periodico
Overdisp: an R package for direct detection of overdispersion in count data multiple regression analysis (2022)
Souza, Rafael de Freitas ; Fávero, Luiz Paulo Lopes ; Belfiore, Patrícia; Corrêa, Hamilton Luiz
Fonte: International Journal of Business Intelligence and Data Mining. Unidades: FEARP, FEA
Assuntos: DADOS DE CONTAGEM, R (SOFTWARE ESTATÍSTICO)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA, Rafael de Freitas et al. Overdisp: an R package for direct detection of overdispersion in count data multiple regression analysis. International Journal of Business Intelligence and Data Mining, v. 20, n. 3, p. 327-344, 2022Tradução . . Acesso em: 06 jul. 2024.
APA
Souza, R. de F., Fávero, L. P. L., Belfiore, P., & Corrêa, H. L. (2022). Overdisp: an R package for direct detection of overdispersion in count data multiple regression analysis. International Journal of Business Intelligence and Data Mining, 20( 3), 327-344. doi:10.1504/IJBIDM.2022.122157
NLM
Souza R de F, Fávero LPL, Belfiore P, Corrêa HL. Overdisp: an R package for direct detection of overdispersion in count data multiple regression analysis. International Journal of Business Intelligence and Data Mining. 2022 ; 20( 3): 327-344.[citado 2024 jul. 06 ]
Vancouver
Souza R de F, Fávero LPL, Belfiore P, Corrêa HL. Overdisp: an R package for direct detection of overdispersion in count data multiple regression analysis. International Journal of Business Intelligence and Data Mining. 2022 ; 20( 3): 327-344.[citado 2024 jul. 06 ]
Artigo de periodico
Count data regression analysis: concepts, overdispersion detection, zero-inflation identification, and applications with R (2021)
Fávero, Luiz Paulo Lopes ; Souza, Rafael de Freitas ; Belfiore, Patrícia Prado; Corrêa, Hamilton Luiz; Haddad, Michel F. C
Fonte: Practical Assessment, Research & Evaluation. Unidade: FEA
Assuntos: ESTATÍSTICA APLICADA, PROBABILIDADE, ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FÁVERO, Luiz Paulo Lopes et al. Count data regression analysis: concepts, overdispersion detection, zero-inflation identification, and applications with R. Practical Assessment, Research & Evaluation, v. 26 , n. Ju 2021, p. 1-22, 2021Tradução . . Disponível em: https://doi.org/10.7275/44nn-cj68. Acesso em: 06 jul. 2024.
APA
Fávero, L. P. L., Souza, R. de F., Belfiore, P. P., Corrêa, H. L., & Haddad, M. F. C. (2021). Count data regression analysis: concepts, overdispersion detection, zero-inflation identification, and applications with R. Practical Assessment, Research & Evaluation, 26 ( Ju 2021), 1-22. doi:10.7275/44nn-cj68
NLM
Fávero LPL, Souza R de F, Belfiore PP, Corrêa HL, Haddad MFC. Count data regression analysis: concepts, overdispersion detection, zero-inflation identification, and applications with R [Internet]. Practical Assessment, Research & Evaluation. 2021 ; 26 ( Ju 2021): 1-22.[citado 2024 jul. 06 ] Available from: https://doi.org/10.7275/44nn-cj68
Vancouver
Fávero LPL, Souza R de F, Belfiore PP, Corrêa HL, Haddad MFC. Count data regression analysis: concepts, overdispersion detection, zero-inflation identification, and applications with R [Internet]. Practical Assessment, Research & Evaluation. 2021 ; 26 ( Ju 2021): 1-22.[citado 2024 jul. 06 ] Available from: https://doi.org/10.7275/44nn-cj68

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