Filtros : "Journal of Statistical Computation and Simulation" "Brasil" Limpar

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

    Subjects: DADOS CENSURADOS, DISTRIBUIÇÕES (ANÁLISE FUNCIONAL), MÉTODOS MCMC

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      RAMOS, Eduardo et al. Posterior properties with censored responses using the gamma distribution. Journal of Statistical Computation and Simulation, v. 95, n. 9, p. 2064-2087, 2025Tradução . . Disponível em: https://doi.org/10.1080/00949655.2025.2479639. Acesso em: 12 nov. 2025.
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      Ramos, E., Ramos, P. L., Leão, J., & Louzada, F. (2025). Posterior properties with censored responses using the gamma distribution. Journal of Statistical Computation and Simulation, 95( 9), 2064-2087. doi:10.1080/00949655.2025.2479639
    • NLM

      Ramos E, Ramos PL, Leão J, Louzada F. Posterior properties with censored responses using the gamma distribution [Internet]. Journal of Statistical Computation and Simulation. 2025 ; 95( 9): 2064-2087.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2025.2479639
    • Vancouver

      Ramos E, Ramos PL, Leão J, Louzada F. Posterior properties with censored responses using the gamma distribution [Internet]. Journal of Statistical Computation and Simulation. 2025 ; 95( 9): 2064-2087.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2025.2479639
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: INFERÊNCIA PARAMÉTRICA

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      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: 12 nov. 2025.
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      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. 12 ] 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. 12 ] Available from: https://doi.org/10.1080/00949655.2024.2361824
  • Source: Journal of Statistical Computation and Simulation. Unidades: ICMC, Interinstitucional de Pós-Graduação em Estatística

    Subjects: DADOS CENSURADOS, ANÁLISE DE SOBREVIVÊNCIA, SIMULAÇÃO, DISTRIBUIÇÕES (PROBABILIDADE)

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      RAMOS, Pedro Luiz et al. Sampling with censored data: a practical guide. Journal of Statistical Computation and Simulation, v. 94, n. 18, p. 4072-4106, 2024Tradução . . Disponível em: https://doi.org/10.1080/00949655.2024.2409379. Acesso em: 12 nov. 2025.
    • APA

      Ramos, P. L., Guzman, D. C. F., Mota, A. L., Saavedra, D., Rodrigues, F. A., & Louzada, F. (2024). Sampling with censored data: a practical guide. Journal of Statistical Computation and Simulation, 94( 18), 4072-4106. doi:10.1080/00949655.2024.2409379
    • NLM

      Ramos PL, Guzman DCF, Mota AL, Saavedra D, Rodrigues FA, Louzada F. Sampling with censored data: a practical guide [Internet]. Journal of Statistical Computation and Simulation. 2024 ; 94( 18): 4072-4106.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2024.2409379
    • Vancouver

      Ramos PL, Guzman DCF, Mota AL, Saavedra D, Rodrigues FA, Louzada F. Sampling with censored data: a practical guide [Internet]. Journal of Statistical Computation and Simulation. 2024 ; 94( 18): 4072-4106.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2024.2409379
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: ESTATÍSTICA APLICADA, TEORIA DA CONFIABILIDADE, RISCO

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      GONZATTO JUNIOR, Oilson Alberto et al. Frailty model for multiple repairable systems hierarchically represented subject to competing risks. Journal of Statistical Computation and Simulation, v. 94, n. 15, p. 3271-3291, 2024Tradução . . Disponível em: https://doi.org/10.1080/00949655.2024.2381515. Acesso em: 12 nov. 2025.
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      Gonzatto Junior, O. A., Fernandes, W. R., Ramos, P. L., Tomazella, V. L. D., & Louzada, F. (2024). Frailty model for multiple repairable systems hierarchically represented subject to competing risks. Journal of Statistical Computation and Simulation, 94( 15), 3271-3291. doi:10.1080/00949655.2024.2381515
    • NLM

      Gonzatto Junior OA, Fernandes WR, Ramos PL, Tomazella VLD, Louzada F. Frailty model for multiple repairable systems hierarchically represented subject to competing risks [Internet]. Journal of Statistical Computation and Simulation. 2024 ; 94( 15): 3271-3291.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2024.2381515
    • Vancouver

      Gonzatto Junior OA, Fernandes WR, Ramos PL, Tomazella VLD, Louzada F. Frailty model for multiple repairable systems hierarchically represented subject to competing risks [Internet]. Journal of Statistical Computation and Simulation. 2024 ; 94( 15): 3271-3291.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2024.2381515
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: ESTATÍSTICA

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      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: 12 nov. 2025.
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      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. 12 ] 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. 12 ] Available from: https://doi.org/10.1080/00949655.2023.2172170
  • Source: Journal of Statistical Computation and Simulation. Unidade: ESALQ

    Subjects: MODELOS MATEMÁTICOS, VEROSSIMILHANÇA, DADOS DE CONTAGEM

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      TACONELI, Cesar Augusto e LARA, Idemauro Antonio Rodrigues de. Discrete Weibull distribution: different estimation methods under ranked set sampling and simple random sampling. Journal of Statistical Computation and Simulation, 2021Tradução . . Disponível em: https://doi.org/10.1080/00949655.2021.2005597. Acesso em: 12 nov. 2025.
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      Taconeli, C. A., & Lara, I. A. R. de. (2021). Discrete Weibull distribution: different estimation methods under ranked set sampling and simple random sampling. Journal of Statistical Computation and Simulation. doi:10.1080/00949655.2021.2005597
    • NLM

      Taconeli CA, Lara IAR de. Discrete Weibull distribution: different estimation methods under ranked set sampling and simple random sampling [Internet]. Journal of Statistical Computation and Simulation. 2021 ;[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2021.2005597
    • Vancouver

      Taconeli CA, Lara IAR de. Discrete Weibull distribution: different estimation methods under ranked set sampling and simple random sampling [Internet]. Journal of Statistical Computation and Simulation. 2021 ;[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2021.2005597
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: ANÁLISE DE SOBREVIVÊNCIA, VEROSSIMILHANÇA, INFERÊNCIA BAYESIANA

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      RAMOS, Pedro Luiz et al. Bayesian analysis of the inverse generalized gamma distribution using objective priors. Journal of Statistical Computation and Simulation, v. 91, n. 4, p. 786-816, 2021Tradução . . Disponível em: https://doi.org/10.1080/00949655.2020.1830991. Acesso em: 12 nov. 2025.
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      Ramos, P. L., Mota, A. L., Ferreira, P. H., Ramos, E., Tomazella, V. L. D., & Louzada, F. (2021). Bayesian analysis of the inverse generalized gamma distribution using objective priors. Journal of Statistical Computation and Simulation, 91( 4), 786-816. doi:10.1080/00949655.2020.1830991
    • NLM

      Ramos PL, Mota AL, Ferreira PH, Ramos E, Tomazella VLD, Louzada F. Bayesian analysis of the inverse generalized gamma distribution using objective priors [Internet]. Journal of Statistical Computation and Simulation. 2021 ; 91( 4): 786-816.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2020.1830991
    • Vancouver

      Ramos PL, Mota AL, Ferreira PH, Ramos E, Tomazella VLD, Louzada F. Bayesian analysis of the inverse generalized gamma distribution using objective priors [Internet]. Journal of Statistical Computation and Simulation. 2021 ; 91( 4): 786-816.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2020.1830991
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: PROCESSOS DE POISSON, SIMULAÇÃO (ESTATÍSTICA), ANÁLISE DE DADOS

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      RAQUEL, Gabriela Cintra et al. A zero-modified Poisson mixed model with generalized random effect. Journal of Statistical Computation and Simulation, v. 91, n. 12, p. 2457-2474, 2021Tradução . . Disponível em: https://doi.org/10.1080/00949655.2021.1898612. Acesso em: 12 nov. 2025.
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      Raquel, G. C., Conceição, K. S., Prates, M. O., & Andrade, M. G. de. (2021). A zero-modified Poisson mixed model with generalized random effect. Journal of Statistical Computation and Simulation, 91( 12), 2457-2474. doi:10.1080/00949655.2021.1898612
    • NLM

      Raquel GC, Conceição KS, Prates MO, Andrade MG de. A zero-modified Poisson mixed model with generalized random effect [Internet]. Journal of Statistical Computation and Simulation. 2021 ; 91( 12): 2457-2474.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2021.1898612
    • Vancouver

      Raquel GC, Conceição KS, Prates MO, Andrade MG de. A zero-modified Poisson mixed model with generalized random effect [Internet]. Journal of Statistical Computation and Simulation. 2021 ; 91( 12): 2457-2474.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2021.1898612
  • Source: Journal of Statistical Computation and Simulation. Unidade: EP

    Subjects: GRÁFICOS, ESTATÍSTICA

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      QUININO, Roberto da Costa et al. A control chart to monitor the process mean based on inspecting attributes using control limits of the traditional X-bar chart. Journal of Statistical Computation and Simulation, v. 90, n. 9, p. 1639-1660, 2020Tradução . . Disponível em: https://doi.org/10.1080/00949655.2020.1741588. Acesso em: 12 nov. 2025.
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      Quinino, R. da C., Ho, L. L., Cruz, F. R. B. da, & Bessegato, L. F. (2020). A control chart to monitor the process mean based on inspecting attributes using control limits of the traditional X-bar chart. Journal of Statistical Computation and Simulation, 90( 9), 1639-1660. doi:10.1080/00949655.2020.1741588
    • NLM

      Quinino R da C, Ho LL, Cruz FRB da, Bessegato LF. A control chart to monitor the process mean based on inspecting attributes using control limits of the traditional X-bar chart [Internet]. Journal of Statistical Computation and Simulation. 2020 ; 90( 9): 1639-1660.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2020.1741588
    • Vancouver

      Quinino R da C, Ho LL, Cruz FRB da, Bessegato LF. A control chart to monitor the process mean based on inspecting attributes using control limits of the traditional X-bar chart [Internet]. Journal of Statistical Computation and Simulation. 2020 ; 90( 9): 1639-1660.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2020.1741588
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: ANÁLISE DE DADOS, REGRESSÃO LOGÍSTICA, ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), MODELOS LINEARES GENERALIZADOS

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      HUAYANAY, Alex de la Cruz et al. Performance of asymmetric links and correction methods for imbalanced data in binary regression. Journal of Statistical Computation and Simulation, v. 89, n. 9, p. 1694-1714, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2019.1593984. Acesso em: 12 nov. 2025.
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      Huayanay, A. de la C., Bazán Guzmán, J. L., Cancho, V. G., & Dey, D. K. (2019). Performance of asymmetric links and correction methods for imbalanced data in binary regression. Journal of Statistical Computation and Simulation, 89( 9), 1694-1714. doi:10.1080/00949655.2019.1593984
    • NLM

      Huayanay A de la C, Bazán Guzmán JL, Cancho VG, Dey DK. Performance of asymmetric links and correction methods for imbalanced data in binary regression [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 9): 1694-1714.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2019.1593984
    • Vancouver

      Huayanay A de la C, Bazán Guzmán JL, Cancho VG, Dey DK. Performance of asymmetric links and correction methods for imbalanced data in binary regression [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 9): 1694-1714.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2019.1593984
  • Source: Journal of Statistical Computation and Simulation. Unidade: ESALQ

    Subjects: REGRESSÃO LINEAR, ÓLEOS VEGETAIS, COPAÍBA, RESINAS VEGETAIS

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      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: 12 nov. 2025.
    • 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 2025 nov. 12 ] 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 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2018.1534116
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: CLUSTERS, ALGORITMOS ÚTEIS E ESPECÍFICOS, DISTRIBUIÇÕES (PROBABILIDADE)

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      SARAIVA, Erlandson Ferreira e PEREIRA, C. A. B e SUZUKI, Adriano Kamimura. A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling. Journal of Statistical Computation and Simulation, v. 89, n. 15, p. 2848-2870, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2019.1643345. Acesso em: 12 nov. 2025.
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      Saraiva, E. F., Pereira, C. A. B., & Suzuki, A. K. (2019). A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling. Journal of Statistical Computation and Simulation, 89( 15), 2848-2870. doi:10.1080/00949655.2019.1643345
    • NLM

      Saraiva EF, Pereira CAB, Suzuki AK. A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 15): 2848-2870.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2019.1643345
    • Vancouver

      Saraiva EF, Pereira CAB, Suzuki AK. A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 15): 2848-2870.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2019.1643345
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: INFERÊNCIA PARAMÉTRICA, INFERÊNCIA BAYESIANA, MÉTODO DE MONTE CARLO, VEROSSIMILHANÇA, TESTES DE HIPÓTESES

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      ZAVALETA, Katherine Elizabeth Coaguila e CANCHO, Vicente Garibay e LEMONTE, Artur José. Likelihood-based tests in zero-inflated power series models. Journal of Statistical Computation and Simulation, v. 89, n. 3, p. 443-460, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2018.1554660. Acesso em: 12 nov. 2025.
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      Zavaleta, K. E. C., Cancho, V. G., & Lemonte, A. J. (2019). Likelihood-based tests in zero-inflated power series models. Journal of Statistical Computation and Simulation, 89( 3), 443-460. doi:10.1080/00949655.2018.1554660
    • NLM

      Zavaleta KEC, Cancho VG, Lemonte AJ. Likelihood-based tests in zero-inflated power series models [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 3): 443-460.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2018.1554660
    • Vancouver

      Zavaleta KEC, Cancho VG, Lemonte AJ. Likelihood-based tests in zero-inflated power series models [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 3): 443-460.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2018.1554660
  • Source: Journal of Statistical Computation and Simulation. Unidades: ESALQ, ICMC

    Subjects: INFERÊNCIA ESTATÍSTICA, ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO

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      HASHIMOTO, Elizabeth Mie 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: 12 nov. 2025.
    • 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 2025 nov. 12 ] 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 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2018.1534116
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: DADOS DE CONTAGEM, TESTES DE HIPÓTESES, DISTRIBUIÇÃO DE POISSON, VEROSSIMILHANÇA, MÉTODO DE MONTE CARLO

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      SANTOS, Daiane de Souza e CANCHO, Vicente Garibay e RODRIGUES, Josemar. Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model. Journal of Statistical Computation and Simulation, v. 89, n. 5, p. 763-775, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2019.1572144. Acesso em: 12 nov. 2025.
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      Santos, D. de S., Cancho, V. G., & Rodrigues, J. (2019). Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model. Journal of Statistical Computation and Simulation, 89( 5), 763-775. doi:10.1080/00949655.2019.1572144
    • NLM

      Santos D de S, Cancho VG, Rodrigues J. Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 5): 763-775.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2019.1572144
    • Vancouver

      Santos D de S, Cancho VG, Rodrigues J. Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 5): 763-775.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2019.1572144
  • Source: Journal of Statistical Computation and Simulation. Unidade: ESALQ

    Subjects: DISTRIBUIÇÕES (PROBABILIDADE), VEROSSIMILHANÇA, REGRESSÃO LINEAR

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      CORDEIRO, Gauss M et al. The Burr XII System of densities: properties, regression model and applications. Journal of Statistical Computation and Simulation, v. 88, n. 3, p. 432-456, 2018Tradução . . Disponível em: https://doi.org/10.1080/00949655.2017.1392524. Acesso em: 12 nov. 2025.
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      Cordeiro, G. M., Yousof, H. M., Ramires, T. G., & Ortega, E. M. M. (2018). The Burr XII System of densities: properties, regression model and applications. Journal of Statistical Computation and Simulation, 88( 3), 432-456. doi:10.1080/00949655.2017.1392524
    • NLM

      Cordeiro GM, Yousof HM, Ramires TG, Ortega EMM. The Burr XII System of densities: properties, regression model and applications [Internet]. Journal of Statistical Computation and Simulation. 2018 ; 88( 3): 432-456.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2017.1392524
    • Vancouver

      Cordeiro GM, Yousof HM, Ramires TG, Ortega EMM. The Burr XII System of densities: properties, regression model and applications [Internet]. Journal of Statistical Computation and Simulation. 2018 ; 88( 3): 432-456.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2017.1392524
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: ESTATÍSTICA

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      MELO, Tatiane F. N e FERRARI, Sílvia Lopes de Paula e PATRIOTA, Alexandre Galvão. Improved hypothesis testing in a general multivariate elliptical model. Journal of Statistical Computation and Simulation, v. 87, n. 7, p. 1416-1428, 2017Tradução . . Disponível em: https://doi.org/10.1080/00949655.2016.1269330. Acesso em: 12 nov. 2025.
    • APA

      Melo, T. F. N., Ferrari, S. L. de P., & Patriota, A. G. (2017). Improved hypothesis testing in a general multivariate elliptical model. Journal of Statistical Computation and Simulation, 87( 7), 1416-1428. doi:10.1080/00949655.2016.1269330
    • NLM

      Melo TFN, Ferrari SL de P, Patriota AG. Improved hypothesis testing in a general multivariate elliptical model [Internet]. Journal of Statistical Computation and Simulation. 2017 ; 87( 7): 1416-1428.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2016.1269330
    • Vancouver

      Melo TFN, Ferrari SL de P, Patriota AG. Improved hypothesis testing in a general multivariate elliptical model [Internet]. Journal of Statistical Computation and Simulation. 2017 ; 87( 7): 1416-1428.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2016.1269330
  • Source: Journal of Statistical Computation and Simulation. Unidade: ESALQ

    Subjects: AMOSTRAGEM, DISTRIBUIÇÃO NORMAL, ESTIMAÇÃO NÃO PARAMÉTRICA, ESTIMAÇÃO PARAMÉTRICA, MÉTODO DE MONTE CARLO, SIMULAÇÃO (ESTATÍSTICA)

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      CONSULIN, Cintia Maestreli et al. Performance of coefficient of variation estimators in ranked set sampling. Journal of Statistical Computation and Simulation, 2017Tradução . . Disponível em: https://doi.org/10.1080/00949655.2017.1381959. Acesso em: 12 nov. 2025.
    • APA

      Consulin, C. M., Ferreira, D., Lara, I. A. R. de, De Lorenzo, A., Di Renzo, L., & Taconeli, C. A. (2017). Performance of coefficient of variation estimators in ranked set sampling. Journal of Statistical Computation and Simulation. doi:10.1080/00949655.2017.1381959
    • NLM

      Consulin CM, Ferreira D, Lara IAR de, De Lorenzo A, Di Renzo L, Taconeli CA. Performance of coefficient of variation estimators in ranked set sampling [Internet]. Journal of Statistical Computation and Simulation. 2017 ;[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2017.1381959
    • Vancouver

      Consulin CM, Ferreira D, Lara IAR de, De Lorenzo A, Di Renzo L, Taconeli CA. Performance of coefficient of variation estimators in ranked set sampling [Internet]. Journal of Statistical Computation and Simulation. 2017 ;[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2017.1381959
  • Source: Journal of Statistical Computation and Simulation. Unidade: ESALQ

    Subjects: DISTRIBUIÇÕES (PROBABILIDADE), MODELOS MATEMÁTICOS, VEROSSIMILHANÇA

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    • ABNT

      ALIZADEH, Morad et al. Odd-Burr generalized family of distributions with some applications. Journal of Statistical Computation and Simulation, v. 87, n. 2, p. 367-389, 2017Tradução . . Disponível em: https://doi.org/10.1080/00949655.2016.1209200. Acesso em: 12 nov. 2025.
    • APA

      Alizadeh, M., Cordeiro, G. M., Nascimento, A. D. C., Lima, M. do C. S., & Ortega, E. M. M. (2017). Odd-Burr generalized family of distributions with some applications. Journal of Statistical Computation and Simulation, 87( 2), 367-389. doi:10.1080/00949655.2016.1209200
    • NLM

      Alizadeh M, Cordeiro GM, Nascimento ADC, Lima M do CS, Ortega EMM. Odd-Burr generalized family of distributions with some applications [Internet]. Journal of Statistical Computation and Simulation. 2017 ; 87( 2): 367-389.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2016.1209200
    • Vancouver

      Alizadeh M, Cordeiro GM, Nascimento ADC, Lima M do CS, Ortega EMM. Odd-Burr generalized family of distributions with some applications [Internet]. Journal of Statistical Computation and Simulation. 2017 ; 87( 2): 367-389.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2016.1209200
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: ESTATÍSTICA, ESTATÍSTICA APLICADA, INFERÊNCIA BAYESIANA

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      GRANZOTTO, D. C. T e LOUZADA, Francisco e BALAKRISHNAN, N. Cubic rank transmuted distributions: inferential issues and applications. Journal of Statistical Computation and Simulation, v. 87, n. 14, p. 2760-2778, 2017Tradução . . Disponível em: https://doi.org/10.1080/00949655.2017.1344239. Acesso em: 12 nov. 2025.
    • APA

      Granzotto, D. C. T., Louzada, F., & Balakrishnan, N. (2017). Cubic rank transmuted distributions: inferential issues and applications. Journal of Statistical Computation and Simulation, 87( 14), 2760-2778. doi:10.1080/00949655.2017.1344239
    • NLM

      Granzotto DCT, Louzada F, Balakrishnan N. Cubic rank transmuted distributions: inferential issues and applications [Internet]. Journal of Statistical Computation and Simulation. 2017 ; 87( 14): 2760-2778.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2017.1344239
    • Vancouver

      Granzotto DCT, Louzada F, Balakrishnan N. Cubic rank transmuted distributions: inferential issues and applications [Internet]. Journal of Statistical Computation and Simulation. 2017 ; 87( 14): 2760-2778.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1080/00949655.2017.1344239

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