Filtros : "Journal of Statistical Computation and Simulation" "IME-MAE" Removido: "1997" Limpar

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  • Source: Journal of Statistical Computation and Simulation. Unidades: IME, EP

    Subjects: DADOS DE CONTAGEM, CONTROLE DE PROCESSOS, ANÁLISE DE SÉRIES TEMPORAIS

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    • ABNT

      SALES, Lucas de Oliveira Ferreira de e ALENCAR, Airlane Pereira e HO, Linda Lee. A modified Shewhart control chart for monitoring the BerG-GARMA model. Journal of Statistical Computation and Simulation, v. 95, n. 9, p. 1993-2009, 2025Tradução . . Disponível em: https://doi.org/10.1080/00949655.2025.2477731. Acesso em: 04 jul. 2025.
    • APA

      Sales, L. de O. F. de, Alencar, A. P., & Ho, L. L. (2025). A modified Shewhart control chart for monitoring the BerG-GARMA model. Journal of Statistical Computation and Simulation, 95( 9), 1993-2009. doi:10.1080/00949655.2025.2477731
    • NLM

      Sales L de OF de, Alencar AP, Ho LL. A modified Shewhart control chart for monitoring the BerG-GARMA model [Internet]. Journal of Statistical Computation and Simulation. 2025 ; 95( 9): 1993-2009.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2025.2477731
    • Vancouver

      Sales L de OF de, Alencar AP, Ho LL. A modified Shewhart control chart for monitoring the BerG-GARMA model [Internet]. Journal of Statistical Computation and Simulation. 2025 ; 95( 9): 1993-2009.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2025.2477731
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: INFERÊNCIA PARAMÉTRICA

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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: 04 jul. 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 jul. 04 ] 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 jul. 04 ] 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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      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: 04 jul. 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 jul. 04 ] 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 jul. 04 ] 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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      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: 04 jul. 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 jul. 04 ] 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 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2021.1955887
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: DISTRIBUIÇÕES (PROBABILIDADE)

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      AL-SHARADQAH, Ali A. e PATRIOTA, Alexandre Galvão. On estimating the boundaries of a uniform distribution under additive measurement errors. Journal of Statistical Computation and Simulation, v. 92, n. 10, p. 2112-2140, 2022Tradução . . Disponível em: https://doi.org/10.1080/00949655.2021.2022149. Acesso em: 04 jul. 2025.
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      Al-Sharadqah, A. A., & Patriota, A. G. (2022). On estimating the boundaries of a uniform distribution under additive measurement errors. Journal of Statistical Computation and Simulation, 92( 10), 2112-2140. doi:10.1080/00949655.2021.2022149
    • NLM

      Al-Sharadqah AA, Patriota AG. On estimating the boundaries of a uniform distribution under additive measurement errors [Internet]. Journal of Statistical Computation and Simulation. 2022 ; 92( 10): 2112-2140.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2021.2022149
    • Vancouver

      Al-Sharadqah AA, Patriota AG. On estimating the boundaries of a uniform distribution under additive measurement errors [Internet]. Journal of Statistical Computation and Simulation. 2022 ; 92( 10): 2112-2140.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2021.2022149
  • Source: Journal of Statistical Computation and Simulation. Unidades: IME, EP

    Subjects: ANALISE DE SÉRIES TEMPORAIS, ANALISE DE REGRESSÃO E DE CORRELAÇÃO

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    • ABNT

      ESPARZA ALBARRACIN, Orlando Yesid e ALENCAR, Airlane Pereira e HO, Linda Lee. Generalized autoregressive and moving average models: multicollinearity, interpretation and a new modified model. Journal of Statistical Computation and Simulation, v. 89, n. 10, p. 1819-1840, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2019.1599892. Acesso em: 04 jul. 2025.
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      Esparza Albarracin, O. Y., Alencar, A. P., & Ho, L. L. (2019). Generalized autoregressive and moving average models: multicollinearity, interpretation and a new modified model. Journal of Statistical Computation and Simulation, 89( 10), 1819-1840. doi:10.1080/00949655.2019.1599892
    • NLM

      Esparza Albarracin OY, Alencar AP, Ho LL. Generalized autoregressive and moving average models: multicollinearity, interpretation and a new modified model [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 10): 1819-1840.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1599892
    • Vancouver

      Esparza Albarracin OY, Alencar AP, Ho LL. Generalized autoregressive and moving average models: multicollinearity, interpretation and a new modified model [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 10): 1819-1840.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1599892
  • 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: 04 jul. 2025.
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      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 jul. 04 ] 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 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2016.1269330
  • 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: 04 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. 04 ] 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. 04 ] Available from: https://doi.org/10.1080/00949655.2015.1081689
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Subjects: ANÁLISE DE SOBREVIVÊNCIA, ROBUSTEZ, DISTRIBUIÇÃO DE POISSON, MELANOMA

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      GALLARDO MATELUNA, Diego Ignacio e BOLFARINE, Heleno e LIMA, Antonio Carlos Pedroso de. An EM algorithm for estimating the destructive weighted Poisson cure rate model. Journal of Statistical Computation and Simulation, v. 86, n. 8, p. 1497-1515, 2016Tradução . . Disponível em: https://doi.org/10.1080/00949655.2015.1071375. Acesso em: 04 jul. 2025.
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      Gallardo Mateluna, D. I., Bolfarine, H., & Lima, A. C. P. de. (2016). An EM algorithm for estimating the destructive weighted Poisson cure rate model. Journal of Statistical Computation and Simulation, 86( 8), 1497-1515. doi:10.1080/00949655.2015.1071375
    • NLM

      Gallardo Mateluna DI, Bolfarine H, Lima ACP de. An EM algorithm for estimating the destructive weighted Poisson cure rate model [Internet]. Journal of Statistical Computation and Simulation. 2016 ; 86( 8): 1497-1515.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2015.1071375
    • Vancouver

      Gallardo Mateluna DI, Bolfarine H, Lima ACP de. An EM algorithm for estimating the destructive weighted Poisson cure rate model [Internet]. Journal of Statistical Computation and Simulation. 2016 ; 86( 8): 1497-1515.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2015.1071375
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: DISTRIBUIÇÕES DE EXTREMOS

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      PINHEIRO, Eliane Cantinho e FERRARI, Sílvia Lopes de Paula. A comparative review of generalizations of the Gumbel extreme value distribution with an application to wind speed data. Journal of Statistical Computation and Simulation, 2015Tradução . . Disponível em: https://doi.org/10.1080/00949655.2015.1107909. Acesso em: 04 jul. 2025.
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      Pinheiro, E. C., & Ferrari, S. L. de P. (2015). A comparative review of generalizations of the Gumbel extreme value distribution with an application to wind speed data. Journal of Statistical Computation and Simulation. doi:10.1080/00949655.2015.1107909
    • NLM

      Pinheiro EC, Ferrari SL de P. A comparative review of generalizations of the Gumbel extreme value distribution with an application to wind speed data [Internet]. Journal of Statistical Computation and Simulation. 2015 ;[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2015.1107909
    • Vancouver

      Pinheiro EC, Ferrari SL de P. A comparative review of generalizations of the Gumbel extreme value distribution with an application to wind speed data [Internet]. Journal of Statistical Computation and Simulation. 2015 ;[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2015.1107909
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: PESQUISA E PLANEJAMENTO ESTATÍSTICO

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      FERRARI, Sílvia Lopes de Paula e PINHEIRO, Eliane Cantinho. Small-sample likelihood inference in extreme-value regression models. Journal of Statistical Computation and Simulation, v. 84, n. 3, p. 582-595, 2014Tradução . . Disponível em: https://doi.org/10.1080/00949655.2012.720686. Acesso em: 04 jul. 2025.
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      Ferrari, S. L. de P., & Pinheiro, E. C. (2014). Small-sample likelihood inference in extreme-value regression models. Journal of Statistical Computation and Simulation, 84( 3), 582-595. doi:10.1080/00949655.2012.720686
    • NLM

      Ferrari SL de P, Pinheiro EC. Small-sample likelihood inference in extreme-value regression models [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 3): 582-595.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2012.720686
    • Vancouver

      Ferrari SL de P, Pinheiro EC. Small-sample likelihood inference in extreme-value regression models [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 3): 582-595.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2012.720686
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Subjects: INFERÊNCIA ESTATÍSTICA, MODELOS NÃO LINEARES

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      ANHOLETO, Tatiana e SANDOVAL, Monica Carneiro e BOTTER, Denise Aparecida. Adjusted Pearson residuals in beta regression models. Journal of Statistical Computation and Simulation, v. 84, n. 5, p. 999-1014, 2014Tradução . . Disponível em: https://doi.org/10.1080/00949655.2012.736993. Acesso em: 04 jul. 2025.
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      Anholeto, T., Sandoval, M. C., & Botter, D. A. (2014). Adjusted Pearson residuals in beta regression models. Journal of Statistical Computation and Simulation, 84( 5), 999-1014. doi:10.1080/00949655.2012.736993
    • NLM

      Anholeto T, Sandoval MC, Botter DA. Adjusted Pearson residuals in beta regression models [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 5): 999-1014.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2012.736993
    • Vancouver

      Anholeto T, Sandoval MC, Botter DA. Adjusted Pearson residuals in beta regression models [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 5): 999-1014.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2012.736993
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Subjects: ESTATÍSTICA COMPUTACIONAL, INFERÊNCIA ESTATÍSTICA, ANÁLISE MULTIVARIADA, DISTRIBUIÇÃO ELÍPTICA

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      MELO, Tatiane F. N e FERRARI, Sílvia Lopes de Paula e PATRIOTA, Alexandre Galvão. Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error. Journal of Statistical Computation and Simulation, v. 84, n. 10, p. 2233-2247, 2014Tradução . . Disponível em: https://doi.org/10.1080/00949655.2013.787691. Acesso em: 04 jul. 2025.
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      Melo, T. F. N., Ferrari, S. L. de P., & Patriota, A. G. (2014). Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error. Journal of Statistical Computation and Simulation, 84( 10), 2233-2247. doi:10.1080/00949655.2013.787691
    • NLM

      Melo TFN, Ferrari SL de P, Patriota AG. Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 10): 2233-2247.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2013.787691
    • Vancouver

      Melo TFN, Ferrari SL de P, Patriota AG. Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error [Internet]. Journal of Statistical Computation and Simulation. 2014 ; 84( 10): 2233-2247.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2013.787691
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: ANÁLISE MULTIVARIADA

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      BLAS, Betsabe e BOLFARINE, Heleno e LACHOS, Victor. H. Statistical analysis of controlled calibration model with replicates. Journal of Statistical Computation and Simulation, v. 83, n. 5, p. 939-959, 2013Tradução . . Disponível em: https://doi.org/10.1080/00949655.2011.643410. Acesso em: 04 jul. 2025.
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      Blas, B., Bolfarine, H., & Lachos, V. H. (2013). Statistical analysis of controlled calibration model with replicates. Journal of Statistical Computation and Simulation, 83( 5), 939-959. doi:10.1080/00949655.2011.643410
    • NLM

      Blas B, Bolfarine H, Lachos VH. Statistical analysis of controlled calibration model with replicates [Internet]. Journal of Statistical Computation and Simulation. 2013 ; 83( 5): 939-959.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2011.643410
    • Vancouver

      Blas B, Bolfarine H, Lachos VH. Statistical analysis of controlled calibration model with replicates [Internet]. Journal of Statistical Computation and Simulation. 2013 ; 83( 5): 939-959.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2011.643410
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: ANÁLISE DE SOBREVIVÊNCIA

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      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: 04 jul. 2025.
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      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. 04 ] 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. 04 ] 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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      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: 04 jul. 2025.
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      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. 04 ] 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. 04 ] Available from: https://doi.org/10.1080/00949655.2011.591798
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: MODELOS (ANÁLISE MULTIVARIADA)

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      FERRARI, Sílvia Lopes de Paula e PINHEIRO, Eliane C. Improved likelihood inference in beta regression. Journal of Statistical Computation and Simulation, v. 81, n. 4, p. 431-443, 2011Tradução . . Disponível em: https://doi.org/10.1080/00949650903389993. Acesso em: 04 jul. 2025.
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      Ferrari, S. L. de P., & Pinheiro, E. C. (2011). Improved likelihood inference in beta regression. Journal of Statistical Computation and Simulation, 81( 4), 431-443. doi:10.1080/00949650903389993
    • NLM

      Ferrari SL de P, Pinheiro EC. Improved likelihood inference in beta regression [Internet]. Journal of Statistical Computation and Simulation. 2011 ; 81( 4): 431-443.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949650903389993
    • Vancouver

      Ferrari SL de P, Pinheiro EC. Improved likelihood inference in beta regression [Internet]. Journal of Statistical Computation and Simulation. 2011 ; 81( 4): 431-443.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949650903389993
  • Source: Journal of Statistical Computation and Simulation. Unidades: ESALQ, IME

    Assunto: DADOS CENSURADOS

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      ORTEGA, Edwin Moisés Marcos e PAULA, Gilberto Alvarenga e BOLFARINE, Heleno. Deviance residuals in generalised log-gamma regression models with censored observations. Journal of Statistical Computation and Simulation, v. 78, n. 8, p. 747-764, 2008Tradução . . Disponível em: https://doi.org/10.1080/00949650701282465. Acesso em: 04 jul. 2025.
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      Ortega, E. M. M., Paula, G. A., & Bolfarine, H. (2008). Deviance residuals in generalised log-gamma regression models with censored observations. Journal of Statistical Computation and Simulation, 78( 8), 747-764. doi:10.1080/00949650701282465
    • NLM

      Ortega EMM, Paula GA, Bolfarine H. Deviance residuals in generalised log-gamma regression models with censored observations [Internet]. Journal of Statistical Computation and Simulation. 2008 ; 78( 8): 747-764.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949650701282465
    • Vancouver

      Ortega EMM, Paula GA, Bolfarine H. Deviance residuals in generalised log-gamma regression models with censored observations [Internet]. Journal of Statistical Computation and Simulation. 2008 ; 78( 8): 747-764.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949650701282465
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: DISTRIBUIÇÃO ELÍPTICA

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    • ABNT

      LEIVA, Victor et al. Random number generators for the generalized Birnbaum-Saunders distribution. Journal of Statistical Computation and Simulation, v. 78, n. 11, p. 1105-1118, 2008Tradução . . Disponível em: https://doi.org/10.1080/00949650701550242. Acesso em: 04 jul. 2025.
    • APA

      Leiva, V., Sanhueza, A., Sen, P. K., & Paula, G. A. (2008). Random number generators for the generalized Birnbaum-Saunders distribution. Journal of Statistical Computation and Simulation, 78( 11), 1105-1118. doi:10.1080/00949650701550242
    • NLM

      Leiva V, Sanhueza A, Sen PK, Paula GA. Random number generators for the generalized Birnbaum-Saunders distribution [Internet]. Journal of Statistical Computation and Simulation. 2008 ; 78( 11): 1105-1118.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949650701550242
    • Vancouver

      Leiva V, Sanhueza A, Sen PK, Paula GA. Random number generators for the generalized Birnbaum-Saunders distribution [Internet]. Journal of Statistical Computation and Simulation. 2008 ; 78( 11): 1105-1118.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949650701550242
  • Source: Journal of Statistical Computation and Simulation. Unidade: IME

    Assunto: INFERÊNCIA ESTATÍSTICA

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    • ABNT

      FERRARI, Sílvia Lopes de Paula e SILVA, Michel Ferreira da e CRIBARI NETO, Francisco. Adjusted profile likelihoods for the weibull shape parameter. Journal of Statistical Computation and Simulation, v. 77, n. 7, p. 531-548, 2007Tradução . . Disponível em: https://doi.org/10.1080/10629360600565160. Acesso em: 04 jul. 2025.
    • APA

      Ferrari, S. L. de P., Silva, M. F. da, & Cribari Neto, F. (2007). Adjusted profile likelihoods for the weibull shape parameter. Journal of Statistical Computation and Simulation, 77( 7), 531-548. doi:10.1080/10629360600565160
    • NLM

      Ferrari SL de P, Silva MF da, Cribari Neto F. Adjusted profile likelihoods for the weibull shape parameter [Internet]. Journal of Statistical Computation and Simulation. 2007 ; 77( 7): 531-548.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/10629360600565160
    • Vancouver

      Ferrari SL de P, Silva MF da, Cribari Neto F. Adjusted profile likelihoods for the weibull shape parameter [Internet]. Journal of Statistical Computation and Simulation. 2007 ; 77( 7): 531-548.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/10629360600565160

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