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Filtros : "Journal of Statistical Computation and Simulation" "Suzuki, Adriano Kamimura" Removido: "2021" Limpar

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  • Artigo de periodico

    A bayesian destructive generalized Waring regression cure model with a variance decomposition and application in colorectal cancer data (2024)

    Rodrigues, Josemar ; Cancho, Vicente Garibay ; Balakrishnan, Narayanaswamy ; Suzuki, Adriano Kamimura

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

    Subjects: ANÁLISE DE SOBREVIVÊNCIA, SISTEMA IMUNE, NEOPLASIAS COLORRETAIS, FATORES DE RISCO

    PrivadoAcesso à fonteDOIHow to cite
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    • ABNT

      RODRIGUES, Josemar et al. A bayesian destructive generalized Waring regression cure model with a variance decomposition and application in colorectal cancer data. Journal of Statistical Computation and Simulation, v. 94, n. 14, p. 3111-3130, 2024Tradução . . Disponível em: https://doi.org/10.1080/00949655.2024.2368887. Acesso em: 03 jul. 2025.

    • APA

      Rodrigues, J., Cancho, V. G., Balakrishnan, N., & Suzuki, A. K. (2024). A bayesian destructive generalized Waring regression cure model with a variance decomposition and application in colorectal cancer data. Journal of Statistical Computation and Simulation, 94( 14), 3111-3130. doi:10.1080/00949655.2024.2368887

    • NLM

      Rodrigues J, Cancho VG, Balakrishnan N, Suzuki AK. A bayesian destructive generalized Waring regression cure model with a variance decomposition and application in colorectal cancer data [Internet]. Journal of Statistical Computation and Simulation. 2024 ; 94( 14): 3111-3130.[citado 2025 jul. 03 ] Available from: https://doi.org/10.1080/00949655.2024.2368887

    • Vancouver

      Rodrigues J, Cancho VG, Balakrishnan N, Suzuki AK. A bayesian destructive generalized Waring regression cure model with a variance decomposition and application in colorectal cancer data [Internet]. Journal of Statistical Computation and Simulation. 2024 ; 94( 14): 3111-3130.[citado 2025 jul. 03 ] Available from: https://doi.org/10.1080/00949655.2024.2368887

  • Artigo de periodico

    A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling (2019)

    Saraiva, Erlandson Ferreira ; Pereira, C. A. B; Suzuki, Adriano Kamimura

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

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

    Versão PublicadaAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      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: 03 jul. 2025.

    • APA

      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 jul. 03 ] 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 jul. 03 ] Available from: https://doi.org/10.1080/00949655.2019.1643345
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