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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: 02 jul. 2025.
    • APA

      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 jul. 02 ] 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 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2025.2479639
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: VEROSSIMILHANÇA, MÉTODO DE MONTE CARLO, MODELAGEM DE DADOS, DADOS DE CONTAGEM

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    • ABNT

      SANTOS, Daiane de Souza e CANCHO, Vicente Garibay. Hypothesis testing for the dispersion parameter of the mean-parametrized COM-Poisson regression. Journal of Statistical Computation and Simulation, 2025Tradução . . Disponível em: https://doi.org/10.1080/00949655.2025.2501172. Acesso em: 02 jul. 2025.
    • APA

      Santos, D. de S., & Cancho, V. G. (2025). Hypothesis testing for the dispersion parameter of the mean-parametrized COM-Poisson regression. Journal of Statistical Computation and Simulation. doi:10.1080/00949655.2025.2501172
    • NLM

      Santos D de S, Cancho VG. Hypothesis testing for the dispersion parameter of the mean-parametrized COM-Poisson regression [Internet]. Journal of Statistical Computation and Simulation. 2025 ;[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2025.2501172
    • Vancouver

      Santos D de S, Cancho VG. Hypothesis testing for the dispersion parameter of the mean-parametrized COM-Poisson regression [Internet]. Journal of Statistical Computation and Simulation. 2025 ;[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2025.2501172
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

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

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      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: 02 jul. 2025.
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      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. 02 ] 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. 02 ] Available from: https://doi.org/10.1080/00949655.2024.2368887
  • 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: 02 jul. 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 jul. 02 ] 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 jul. 02 ] 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: 02 jul. 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 jul. 02 ] 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 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2024.2381515
  • 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: 02 jul. 2025.
    • APA

      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 jul. 02 ] 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 jul. 02 ] 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: 02 jul. 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 jul. 02 ] 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 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2021.1898612
  • 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: 02 jul. 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 jul. 02 ] 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. 02 ] 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: 02 jul. 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 jul. 02 ] 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 jul. 02 ] 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: 02 jul. 2025.
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      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 jul. 02 ] 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 jul. 02 ] 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: 02 jul. 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 jul. 02 ] 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 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2019.1572144
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Subjects: INFERÊNCIA PARAMÉTRICA, MÉTODOS PROBABILÍSTICOS, ANÁLISE NUMÉRICA, MÉTODOS GRÁFICOS

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      ANDRADE, B. B de e BOLFARINE, Heleno e SIROKY, A. N. Random number generation and estimation with the bimodal asymmetric power-normal distribution. Journal of Statistical Computation and Simulation, v. 86, n. 3, p. 460-476, 2016Tradução . . Disponível em: https://doi.org/10.1080/00949655.2015.1016434. Acesso em: 02 jul. 2025.
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      Andrade, B. B. de, Bolfarine, H., & Siroky, A. N. (2016). Random number generation and estimation with the bimodal asymmetric power-normal distribution. Journal of Statistical Computation and Simulation, 86( 3), 460-476. doi:10.1080/00949655.2015.1016434
    • NLM

      Andrade BB de, Bolfarine H, Siroky AN. Random number generation and estimation with the bimodal asymmetric power-normal distribution [Internet]. Journal of Statistical Computation and Simulation. 2016 ; 86( 3): 460-476.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2015.1016434
    • Vancouver

      Andrade BB de, Bolfarine H, Siroky AN. Random number generation and estimation with the bimodal asymmetric power-normal distribution [Internet]. Journal of Statistical Computation and Simulation. 2016 ; 86( 3): 460-476.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2015.1016434
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Subjects: ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO NÃO LINEAR, ANÁLISE ESTATÍSTICA DE DADOS, R (SOFTWARE ESTATÍSTICO)

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      VANEGAS, Luis Hernando e PAULA, Gilberto Alvarenga. An extension of log-symmetric regression models: R codes and applications. Journal of Statistical Computation and Simulation, v. 86, n. 9, p. 1709-1735, 2016Tradução . . Disponível em: https://doi.org/10.1080/00949655.2015.1081689. Acesso em: 02 jul. 2025.
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      Vanegas, L. H., & Paula, G. A. (2016). An extension of log-symmetric regression models: R codes and applications. Journal of Statistical Computation and Simulation, 86( 9), 1709-1735. doi:10.1080/00949655.2015.1081689
    • NLM

      Vanegas LH, Paula GA. An extension of log-symmetric regression models: R codes and applications [Internet]. Journal of Statistical Computation and Simulation. 2016 ; 86( 9): 1709-1735.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2015.1081689
    • Vancouver

      Vanegas LH, Paula GA. An extension of log-symmetric regression models: R codes and applications [Internet]. Journal of Statistical Computation and Simulation. 2016 ; 86( 9): 1709-1735.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2015.1081689
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Subjects: INFERÊNCIA ESTATÍSTICA, INFERÊNCIA PARAMÉTRICA

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      FERREIRA, Clécio da Silva e LACHOS, Victor Hugo e BOLFARINE, Heleno. Inference and diagnostics in skew scale mixtures of normal regression models. Journal of Statistical Computation and Simulation, v. 85, n. 3, p. 517-537, 2015Tradução . . Disponível em: https://doi.org/10.1080/00949655.2013.828057. Acesso em: 02 jul. 2025.
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      Ferreira, C. da S., Lachos, V. H., & Bolfarine, H. (2015). Inference and diagnostics in skew scale mixtures of normal regression models. Journal of Statistical Computation and Simulation, 85( 3), 517-537. doi:10.1080/00949655.2013.828057
    • NLM

      Ferreira C da S, Lachos VH, Bolfarine H. Inference and diagnostics in skew scale mixtures of normal regression models [Internet]. Journal of Statistical Computation and Simulation. 2015 ; 85( 3): 517-537.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2013.828057
    • Vancouver

      Ferreira C da S, Lachos VH, Bolfarine H. Inference and diagnostics in skew scale mixtures of normal regression models [Internet]. Journal of Statistical Computation and Simulation. 2015 ; 85( 3): 517-537.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2013.828057
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Subjects: REGRESSÃO LINEAR, INFERÊNCIA BAYESIANA

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      SANTOS, Bruno e BOLFARINE, Heleno. Bayesian analysis for zero-or-one inflated proportion data using quantile regression. Journal of Statistical Computation and Simulation, v. 85, n. 17, p. 3579-3593, 2015Tradução . . Disponível em: https://doi.org/10.1080/00949655.2014.986733. Acesso em: 02 jul. 2025.
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      Santos, B., & Bolfarine, H. (2015). Bayesian analysis for zero-or-one inflated proportion data using quantile regression. Journal of Statistical Computation and Simulation, 85( 17), 3579-3593. doi:10.1080/00949655.2014.986733
    • NLM

      Santos B, Bolfarine H. Bayesian analysis for zero-or-one inflated proportion data using quantile regression [Internet]. Journal of Statistical Computation and Simulation. 2015 ; 85( 17): 3579-3593.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2014.986733
    • Vancouver

      Santos B, Bolfarine H. Bayesian analysis for zero-or-one inflated proportion data using quantile regression [Internet]. Journal of Statistical Computation and Simulation. 2015 ; 85( 17): 3579-3593.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2014.986733
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

    Subjects: ANÁLISE DE SOBREVIVÊNCIA, DISTRIBUIÇÕES (PROBABILIDADE), ESTATÍSTICA APLICADA

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      TOJEIRO, Cynthia A. V et al. The complementaryWeibull geometric distribution. Journal of Statistical Computation and Simulation, v. 84, n. 6, p. 1345-1362, 2014Tradução . . Disponível em: https://doi.org/10.1080/00949655.2012.744406. Acesso em: 02 jul. 2025.
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      Tojeiro, C. A. V., Louzada, F., Roman, M., & Borges, P. (2014). The complementaryWeibull geometric distribution. Journal of Statistical Computation and Simulation, 84( 6), 1345-1362. doi:10.1080/00949655.2012.744406
    • NLM

      Tojeiro CAV, Louzada F, Roman M, Borges P. The complementaryWeibull geometric distribution [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 6): 1345-1362.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2012.744406
    • Vancouver

      Tojeiro CAV, Louzada F, Roman M, Borges P. The complementaryWeibull geometric distribution [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 6): 1345-1362.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2012.744406
  • Source: Journal of Statistical Computation and Simulation. Unidade: ICMC

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

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      TOJEIRO, Cynthia et al. The complementary Weibull geometric distribution. Journal of Statistical Computation and Simulation, v. 84, n. 6, p. 1345-1362, 2014Tradução . . Disponível em: https://doi.org/10.1080/00949655.2012.744406. Acesso em: 02 jul. 2025.
    • APA

      Tojeiro, C., Louzada, F., Roman, M., & Borges, P. (2014). The complementary Weibull geometric distribution. Journal of Statistical Computation and Simulation, 84( 6), 1345-1362. doi:10.1080/00949655.2012.744406
    • NLM

      Tojeiro C, Louzada F, Roman M, Borges P. The complementary Weibull geometric distribution [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 6): 1345-1362.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2012.744406
    • Vancouver

      Tojeiro C, Louzada F, Roman M, Borges P. The complementary Weibull geometric distribution [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 6): 1345-1362.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2012.744406
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: ANÁLISE DE SOBREVIVÊNCIA

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    • ABNT

      FONSECA, Renata Santana e VALENÇA, Dione Maria e BOLFARINE, Heleno. Cure rate survival models with missing covariates: a simulation study. Journal of Statistical Computation and Simulation, v. 63, n. 1, p. 97-113, 2013Tradução . . Disponível em: https://doi.org/10.1080/00949655.2011.613396. Acesso em: 02 jul. 2025.
    • APA

      Fonseca, R. S., Valença, D. M., & Bolfarine, H. (2013). Cure rate survival models with missing covariates: a simulation study. Journal of Statistical Computation and Simulation, 63( 1), 97-113. doi:10.1080/00949655.2011.613396
    • NLM

      Fonseca RS, Valença DM, Bolfarine H. Cure rate survival models with missing covariates: a simulation study [Internet]. Journal of Statistical Computation and Simulation. 2013 ; 63( 1): 97-113.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2011.613396
    • Vancouver

      Fonseca RS, Valença DM, Bolfarine H. Cure rate survival models with missing covariates: a simulation study [Internet]. Journal of Statistical Computation and Simulation. 2013 ; 63( 1): 97-113.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2011.613396
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: DISTRIBUIÇÕES (PROBABILIDADE)

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    • ABNT

      AZEVEDO, Caio L.N e BOLFARINE, Heleno e ANDRADE, Dalton Francisco de. Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size. Journal of Statistical Computation and Simulation, v. 82, n. 11, p. 1679-1699, 2012Tradução . . Disponível em: https://doi.org/10.1080/00949655.2011.591798. Acesso em: 02 jul. 2025.
    • APA

      Azevedo, C. L. N., Bolfarine, H., & Andrade, D. F. de. (2012). Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size. Journal of Statistical Computation and Simulation, 82( 11), 1679-1699. doi:10.1080/00949655.2011.591798
    • NLM

      Azevedo CLN, Bolfarine H, Andrade DF de. Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size [Internet]. Journal of Statistical Computation and Simulation. 2012 ; 82( 11): 1679-1699.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2011.591798
    • Vancouver

      Azevedo CLN, Bolfarine H, Andrade DF de. Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size [Internet]. Journal of Statistical Computation and Simulation. 2012 ; 82( 11): 1679-1699.[citado 2025 jul. 02 ] Available from: https://doi.org/10.1080/00949655.2011.591798

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