Filtros : "Journal of Statistical Computation and Simulation" "Financiamento CNPq" Removido: "Reino Unido" Limpar

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  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: INFERÊNCIA PARAMÉTRICA

    Versão AceitaAcesso à fonteDOIHow to cite
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    • ABNT

      MELO, Tatiane F. N. et al. Higher-order asymptotic refinements in a multivariate regression model with general parameterization. Journal of Statistical Computation and Simulation, v. 94, n. 13, p. 2952–2975, 2024Tradução . . Disponível em: https://doi.org/10.1080/00949655.2024.2361824. Acesso em: 28 nov. 2025.
    • APA

      Melo, T. F. N., Vargas, T. M., Lemonte, A. J., & Patriota, A. G. (2024). Higher-order asymptotic refinements in a multivariate regression model with general parameterization. Journal of Statistical Computation and Simulation, 94( 13), 2952–2975. doi:10.1080/00949655.2024.2361824
    • NLM

      Melo TFN, Vargas TM, Lemonte AJ, Patriota AG. Higher-order asymptotic refinements in a multivariate regression model with general parameterization [Internet]. Journal of Statistical Computation and Simulation. 2024 ; 94( 13): 2952–2975.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1080/00949655.2024.2361824
    • Vancouver

      Melo TFN, Vargas TM, Lemonte AJ, Patriota AG. Higher-order asymptotic refinements in a multivariate regression model with general parameterization [Internet]. Journal of Statistical Computation and Simulation. 2024 ; 94( 13): 2952–2975.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1080/00949655.2024.2361824
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: ESTATÍSTICA

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    • ABNT

      BARROS, Fabiana U. et al. Improved gradient statistic in heteroskedastic generalized linear models. Journal of Statistical Computation and Simulation, v. 93, n. 12, p. 2052-2066, 2023Tradução . . Disponível em: https://doi.org/10.1080/00949655.2023.2172170. Acesso em: 28 nov. 2025.
    • APA

      Barros, F. U., Botter, D. A., Sandoval, M. C., & Magalhães, T. M. (2023). Improved gradient statistic in heteroskedastic generalized linear models. Journal of Statistical Computation and Simulation, 93( 12), 2052-2066. doi:10.1080/00949655.2023.2172170
    • NLM

      Barros FU, Botter DA, Sandoval MC, Magalhães TM. Improved gradient statistic in heteroskedastic generalized linear models [Internet]. Journal of Statistical Computation and Simulation. 2023 ; 93( 12): 2052-2066.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1080/00949655.2023.2172170
    • Vancouver

      Barros FU, Botter DA, Sandoval MC, Magalhães TM. Improved gradient statistic in heteroskedastic generalized linear models [Internet]. Journal of Statistical Computation and Simulation. 2023 ; 93( 12): 2052-2066.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1080/00949655.2023.2172170
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Subjects: ANÁLISE DE SÉRIES TEMPORAIS, DISTRIBUIÇÕES (PROBABILIDADE)

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    • ABNT

      MELO, Moizes da Silva e ALENCAR, Airlane Pereira. Conway-Maxwell-Poisson seasonal autoregressive moving average model. Journal of Statistical Computation and Simulation, v. 92, n. 2, p. 283-299, 2022Tradução . . Disponível em: https://doi.org/10.1080/00949655.2021.1955887. Acesso em: 28 nov. 2025.
    • APA

      Melo, M. da S., & Alencar, A. P. (2022). Conway-Maxwell-Poisson seasonal autoregressive moving average model. Journal of Statistical Computation and Simulation, 92( 2), 283-299. doi:10.1080/00949655.2021.1955887
    • NLM

      Melo M da S, Alencar AP. Conway-Maxwell-Poisson seasonal autoregressive moving average model [Internet]. Journal of Statistical Computation and Simulation. 2022 ; 92( 2): 283-299.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1080/00949655.2021.1955887
    • Vancouver

      Melo M da S, Alencar AP. Conway-Maxwell-Poisson seasonal autoregressive moving average model [Internet]. Journal of Statistical Computation and Simulation. 2022 ; 92( 2): 283-299.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1080/00949655.2021.1955887

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