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  • Artigo de periodico

    New statistical process control charts for overdispersed count data based on the Bell distribution (2023)

    Boaventura, Laion Lima ; Ferreira, Paulo Henrique ; Fiaccone, Rosemeire L ; Ramos, Pedro Luiz ; Louzada, Francisco

    Unidade: ICMC

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

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

    • ABNT

      BOAVENTURA, Laion Lima et al. New statistical process control charts for overdispersed count data based on the Bell distribution. v. 95, n. 2, p. 1-22, 2023Tradução . . Disponível em: https://doi.org/10.1590/0001-3765202320200246. Acesso em: 04 jan. 2026.

    • APA

      Boaventura, L. L., Ferreira, P. H., Fiaccone, R. L., Ramos, P. L., & Louzada, F. (2023). New statistical process control charts for overdispersed count data based on the Bell distribution, 95( 2), 1-22. doi:10.1590/0001-3765202320200246

    • NLM

      Boaventura LL, Ferreira PH, Fiaccone RL, Ramos PL, Louzada F. New statistical process control charts for overdispersed count data based on the Bell distribution [Internet]. 2023 ; 95( 2): 1-22.[citado 2026 jan. 04 ] Available from: https://doi.org/10.1590/0001-3765202320200246

    • Vancouver

      Boaventura LL, Ferreira PH, Fiaccone RL, Ramos PL, Louzada F. New statistical process control charts for overdispersed count data based on the Bell distribution [Internet]. 2023 ; 95( 2): 1-22.[citado 2026 jan. 04 ] Available from: https://doi.org/10.1590/0001-3765202320200246

  • Artigo de periodico

    Statistical process control of overdispersed count data based on one-parameter Poisson mixture models (2022)

    Jesus, Bruno D; Ferreira, Paulo Henrique ; Boaventura, Laion Lima ; Fiaccone, Rosemeire L ; Silva, Wesley Bertoli da ; Ramos, Pedro Luiz ; Louzada, Francisco

    Source: Quality and Reliability Engineering International. Unidade: ICMC

    Subjects: PROCESSOS DE POISSON, DISTRIBUIÇÕES (PROBABILIDADE), DADOS DE CONTAGEM

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

    • ABNT

      JESUS, Bruno D et al. Statistical process control of overdispersed count data based on one-parameter Poisson mixture models. Quality and Reliability Engineering International, v. 38, n. 5, p. 2324-2344, 2022Tradução . . Disponível em: https://doi.org/10.1002/qre.3077. Acesso em: 04 jan. 2026.

    • APA

      Jesus, B. D., Ferreira, P. H., Boaventura, L. L., Fiaccone, R. L., Silva, W. B. da, Ramos, P. L., & Louzada, F. (2022). Statistical process control of overdispersed count data based on one-parameter Poisson mixture models. Quality and Reliability Engineering International, 38( 5), 2324-2344. doi:10.1002/qre.3077

    • NLM

      Jesus BD, Ferreira PH, Boaventura LL, Fiaccone RL, Silva WB da, Ramos PL, Louzada F. Statistical process control of overdispersed count data based on one-parameter Poisson mixture models [Internet]. Quality and Reliability Engineering International. 2022 ; 38( 5): 2324-2344.[citado 2026 jan. 04 ] Available from: https://doi.org/10.1002/qre.3077

    • Vancouver

      Jesus BD, Ferreira PH, Boaventura LL, Fiaccone RL, Silva WB da, Ramos PL, Louzada F. Statistical process control of overdispersed count data based on one-parameter Poisson mixture models [Internet]. Quality and Reliability Engineering International. 2022 ; 38( 5): 2324-2344.[citado 2026 jan. 04 ] Available from: https://doi.org/10.1002/qre.3077

  • Artigo de periodico

    CUSUM chart to monitor autocorrelated counts using negative binomial GARMA model (2018)

    Esparza Albarracin, Orlando Yesid ; Alencar, Airlane Pereira ; Ho, Linda Lee

    Source: Statistical Methods in Medical Research. Unidades: IME, EP

    Subjects: ESTATÍSTICA APLICADA, ANÁLISE DE SÉRIES TEMPORAIS

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

    • ABNT

      ESPARZA ALBARRACIN, Orlando Yesid e ALENCAR, Airlane Pereira e HO, Linda Lee. CUSUM chart to monitor autocorrelated counts using negative binomial GARMA model. Statistical Methods in Medical Research, v. 27, n. 9, p. 2859–2871, 2018Tradução . . Disponível em: https://doi.org/10.1177/0962280216686627. Acesso em: 04 jan. 2026.

    • APA

      Esparza Albarracin, O. Y., Alencar, A. P., & Ho, L. L. (2018). CUSUM chart to monitor autocorrelated counts using negative binomial GARMA model. Statistical Methods in Medical Research, 27( 9), 2859–2871. doi:10.1177/0962280216686627

    • NLM

      Esparza Albarracin OY, Alencar AP, Ho LL. CUSUM chart to monitor autocorrelated counts using negative binomial GARMA model [Internet]. Statistical Methods in Medical Research. 2018 ; 27( 9): 2859–2871.[citado 2026 jan. 04 ] Available from: https://doi.org/10.1177/0962280216686627

    • Vancouver

      Esparza Albarracin OY, Alencar AP, Ho LL. CUSUM chart to monitor autocorrelated counts using negative binomial GARMA model [Internet]. Statistical Methods in Medical Research. 2018 ; 27( 9): 2859–2871.[citado 2026 jan. 04 ] Available from: https://doi.org/10.1177/0962280216686627
  • 1

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