Filtros : "Communications in Statistics - Simulation and Computation" "VEROSSIMILHANÇA" Removido: "ESALQ" Limpar

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  • Source: Communications in Statistics - Simulation and Computation. Unidades: ICMC, Interinstitucional de Pós-Graduação em Estatística

    Subjects: ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, VEROSSIMILHANÇA, MÉTODO DE MONTE CARLO

    PrivadoAcesso à fonteDOIHow to cite
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    • ABNT

      MOTA, Alex Leal et al. Weighted Lindley regression model with varying precision: estimation, modeling and its diagnostics. Communications in Statistics - Simulation and Computation, v. 53, n. 4, p. 1690-1710, 2024Tradução . . Disponível em: https://doi.org/10.1080/03610918.2022.2053719. Acesso em: 01 dez. 2025.
    • APA

      Mota, A. L., Santos-Neto, M., Miranda Neto, M., Leão, J., Tomazella, V. L. D., & Louzada, F. (2024). Weighted Lindley regression model with varying precision: estimation, modeling and its diagnostics. Communications in Statistics - Simulation and Computation, 53( 4), 1690-1710. doi:10.1080/03610918.2022.2053719
    • NLM

      Mota AL, Santos-Neto M, Miranda Neto M, Leão J, Tomazella VLD, Louzada F. Weighted Lindley regression model with varying precision: estimation, modeling and its diagnostics [Internet]. Communications in Statistics - Simulation and Computation. 2024 ; 53( 4): 1690-1710.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1080/03610918.2022.2053719
    • Vancouver

      Mota AL, Santos-Neto M, Miranda Neto M, Leão J, Tomazella VLD, Louzada F. Weighted Lindley regression model with varying precision: estimation, modeling and its diagnostics [Internet]. Communications in Statistics - Simulation and Computation. 2024 ; 53( 4): 1690-1710.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1080/03610918.2022.2053719
  • Source: Communications in Statistics - Simulation and Computation. Unidade: ICMC

    Subjects: DISTRIBUIÇÕES (PROBABILIDADE), VEROSSIMILHANÇA, SIMULAÇÃO (ESTATÍSTICA)

    Versão AceitaAcesso à fonteDOIHow to cite
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    • ABNT

      CHESNEAU, Christophe et al. The polynomial-exponential distribution: a continuous probability model allowing for occurrence of zero values. Communications in Statistics - Simulation and Computation, v. 51, n. 8, p. 4581-4606, 2022Tradução . . Disponível em: https://doi.org/10.1080/03610918.2020.1746339. Acesso em: 01 dez. 2025.
    • APA

      Chesneau, C., Bakouch, H. S., Ramos, P. L., & Louzada, F. (2022). The polynomial-exponential distribution: a continuous probability model allowing for occurrence of zero values. Communications in Statistics - Simulation and Computation, 51( 8), 4581-4606. doi:10.1080/03610918.2020.1746339
    • NLM

      Chesneau C, Bakouch HS, Ramos PL, Louzada F. The polynomial-exponential distribution: a continuous probability model allowing for occurrence of zero values [Internet]. Communications in Statistics - Simulation and Computation. 2022 ; 51( 8): 4581-4606.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1080/03610918.2020.1746339
    • Vancouver

      Chesneau C, Bakouch HS, Ramos PL, Louzada F. The polynomial-exponential distribution: a continuous probability model allowing for occurrence of zero values [Internet]. Communications in Statistics - Simulation and Computation. 2022 ; 51( 8): 4581-4606.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1080/03610918.2020.1746339
  • Source: Communications in Statistics - Simulation and Computation. Unidade: ICMC

    Subjects: DISTRIBUIÇÕES (PROBABILIDADE), VEROSSIMILHANÇA, ESTIMAÇÃO PARAMÉTRICA, METEOROLOGIA

    Versão AceitaAcesso à fonteDOIHow to cite
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    • ABNT

      LOUZADA, Francisco e RAMOS, Pedro Luiz e FERREIRA, Paulo Henrique. Exponential-Poisson distribution: estimation and applications to rainfall and aircraft data with zero occurrence. Communications in Statistics - Simulation and Computation, v. 49, n. 4, p. 1024-1043, 2020Tradução . . Disponível em: https://doi.org/10.1080/03610918.2018.1491988. Acesso em: 01 dez. 2025.
    • APA

      Louzada, F., Ramos, P. L., & Ferreira, P. H. (2020). Exponential-Poisson distribution: estimation and applications to rainfall and aircraft data with zero occurrence. Communications in Statistics - Simulation and Computation, 49( 4), 1024-1043. doi:10.1080/03610918.2018.1491988
    • NLM

      Louzada F, Ramos PL, Ferreira PH. Exponential-Poisson distribution: estimation and applications to rainfall and aircraft data with zero occurrence [Internet]. Communications in Statistics - Simulation and Computation. 2020 ; 49( 4): 1024-1043.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1080/03610918.2018.1491988
    • Vancouver

      Louzada F, Ramos PL, Ferreira PH. Exponential-Poisson distribution: estimation and applications to rainfall and aircraft data with zero occurrence [Internet]. Communications in Statistics - Simulation and Computation. 2020 ; 49( 4): 1024-1043.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1080/03610918.2018.1491988
  • Source: Communications in Statistics - Simulation and Computation. Unidade: ICMC

    Subjects: DISTRIBUIÇÕES (PROBABILIDADE), VEROSSIMILHANÇA

    Acesso à fonteDOIHow to cite
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    • ABNT

      DEY, Sanku et al. Exponentiated chen distribution: properties and estimation. Communications in Statistics - Simulation and Computation, v. 46, n. 10, p. 8118-8139, 2017Tradução . . Disponível em: https://doi.org/10.1080/03610918.2016.1267752. Acesso em: 01 dez. 2025.
    • APA

      Dey, S., Kumar, D., Ramos, P. L., & Louzada, F. (2017). Exponentiated chen distribution: properties and estimation. Communications in Statistics - Simulation and Computation, 46( 10), 8118-8139. doi:10.1080/03610918.2016.1267752
    • NLM

      Dey S, Kumar D, Ramos PL, Louzada F. Exponentiated chen distribution: properties and estimation [Internet]. Communications in Statistics - Simulation and Computation. 2017 ; 46( 10): 8118-8139.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1080/03610918.2016.1267752
    • Vancouver

      Dey S, Kumar D, Ramos PL, Louzada F. Exponentiated chen distribution: properties and estimation [Internet]. Communications in Statistics - Simulation and Computation. 2017 ; 46( 10): 8118-8139.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1080/03610918.2016.1267752

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