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Filtros : "Communications in Statistics - Simulation and Computation" "2018" Removido: "Financiamento CAPES" Limpar

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  • Artigo de periodico

    The heteroscedastic odd log-logistic generalized gamma regression model for censored data (2018)

    Prataviera, Fábio; Ortega, Edwin Moises Marcos; Cordeiro, Gauss M; Braga, Altemir da Silva

    Source: Communications in Statistics - Simulation and Computation. Unidade: ESALQ

    Subjects: ANÁLISE DE SOBREVIVÊNCIA, DADOS CENSURADOS, DISTRIBUIÇÕES (PROBABILIDADE), HETEROSCEDASTICIDADE, MODELOS MATEMÁTICOS

    PrivadoAcesso à fonteDOIHow to cite
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    • ABNT

      PRATAVIERA, Fábio et al. The heteroscedastic odd log-logistic generalized gamma regression model for censored data. Communications in Statistics - Simulation and Computation, p. 1-25, 2018Tradução . . Disponível em: https://doi.org/10.1080/03610918.2018.1423695. Acesso em: 05 jul. 2025.

    • APA

      Prataviera, F., Ortega, E. M. M., Cordeiro, G. M., & Braga, A. da S. (2018). The heteroscedastic odd log-logistic generalized gamma regression model for censored data. Communications in Statistics - Simulation and Computation, 1-25. doi:10.1080/03610918.2018.1423695

    • NLM

      Prataviera F, Ortega EMM, Cordeiro GM, Braga A da S. The heteroscedastic odd log-logistic generalized gamma regression model for censored data [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 1-25.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2018.1423695

    • Vancouver

      Prataviera F, Ortega EMM, Cordeiro GM, Braga A da S. The heteroscedastic odd log-logistic generalized gamma regression model for censored data [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 1-25.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2018.1423695

  • Artigo de periodico

    New regression model with four regression structures and computational aspects (2018)

    Ramires, Thiago Gentil; Ortega, Edwin Moisés Marcos; Cordeiro, Gauss Moutinho ; Paula, Gilberto Alvarenga ; Hens, Niel

    Source: Communications in Statistics - Simulation and Computation. Unidades: ESALQ, IME

    Subjects: REGRESSÃO LINEAR, ANÁLISE DE SOBREVIVÊNCIA, DADOS CENSURADOS, MÉTODO DE CAUCHY, MÉTODOS DE DIAGNÓSTICOS

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    • ABNT

      RAMIRES, Thiago Gentil et al. New regression model with four regression structures and computational aspects. Communications in Statistics - Simulation and Computation, v. 47, n. 7, p. 1940-1962, 2018Tradução . . Disponível em: https://doi.org/10.1080/03610918.2017.1332212. Acesso em: 05 jul. 2025.

    • APA

      Ramires, T. G., Ortega, E. M. M., Cordeiro, G. M., Paula, G. A., & Hens, N. (2018). New regression model with four regression structures and computational aspects. Communications in Statistics - Simulation and Computation, 47( 7), 1940-1962. doi:10.1080/03610918.2017.1332212

    • NLM

      Ramires TG, Ortega EMM, Cordeiro GM, Paula GA, Hens N. New regression model with four regression structures and computational aspects [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 47( 7): 1940-1962.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2017.1332212

    • Vancouver

      Ramires TG, Ortega EMM, Cordeiro GM, Paula GA, Hens N. New regression model with four regression structures and computational aspects [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 47( 7): 1940-1962.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2017.1332212

  • Artigo de periodico

    Global and local tests to assess stationarity of Markov transition models (2018)

    Lara, Idemauro Antonio Rodrigues de; Hinde, John; Taconeli, Cesar Augusto

    Source: Communications in Statistics - Simulation and Computation. Unidade: ESALQ

    Subjects: MODELOS LINEARES GENERALIZADOS, DADOS CATEGORIZADOS, PROCESSOS DE MARKOV, VEROSSIMILHANÇA

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    • ABNT

      LARA, Idemauro Antonio Rodrigues de e HINDE, John e TACONELI, Cesar Augusto. Global and local tests to assess stationarity of Markov transition models. Communications in Statistics - Simulation and Computation, p. 1-21, 2018Tradução . . Disponível em: https://doi.org/10.1080/03610918.2017.1406504. Acesso em: 05 jul. 2025.

    • APA

      Lara, I. A. R. de, Hinde, J., & Taconeli, C. A. (2018). Global and local tests to assess stationarity of Markov transition models. Communications in Statistics - Simulation and Computation, 1-21. doi:10.1080/03610918.2017.1406504

    • NLM

      Lara IAR de, Hinde J, Taconeli CA. Global and local tests to assess stationarity of Markov transition models [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 1-21.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2017.1406504

    • Vancouver

      Lara IAR de, Hinde J, Taconeli CA. Global and local tests to assess stationarity of Markov transition models [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 1-21.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2017.1406504

  • Artigo de periodico

    A class of beta regression models with multiplicative log-normal measurement errors (2018)

    Silva, Eveliny Barroso da; Diniz, Carlos Alberto Ribeiro; Carrasco, Jalmar Manuel Farfan; Castro, Mário de

    Source: Communications in Statistics - Simulation and Computation. Unidade: ICMC

    Assunto: REGRESSÃO

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    • ABNT

      SILVA, Eveliny Barroso da et al. A class of beta regression models with multiplicative log-normal measurement errors. Communications in Statistics - Simulation and Computation, v. 47, n. 1, p. 229-248, 2018Tradução . . Disponível em: https://doi.org/10.1080/03610918.2017.1280165. Acesso em: 05 jul. 2025.

    • APA

      Silva, E. B. da, Diniz, C. A. R., Carrasco, J. M. F., & Castro, M. de. (2018). A class of beta regression models with multiplicative log-normal measurement errors. Communications in Statistics - Simulation and Computation, 47( 1), 229-248. doi:10.1080/03610918.2017.1280165

    • NLM

      Silva EB da, Diniz CAR, Carrasco JMF, Castro M de. A class of beta regression models with multiplicative log-normal measurement errors [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 47( 1): 229-248.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2017.1280165

    • Vancouver

      Silva EB da, Diniz CAR, Carrasco JMF, Castro M de. A class of beta regression models with multiplicative log-normal measurement errors [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 47( 1): 229-248.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2017.1280165

  • Artigo de periodico

    The Kumaraswamy normal linear regression model with applications (2018)

    Cordeiro, Gauss Moutinho ; Machado, Elizabete C; Botter, Denise Aparecida ; Sandoval, Monica Carneiro

    Source: Communications in Statistics - Simulation and Computation. Unidade: IME

    Subjects: INFERÊNCIA ESTATÍSTICA, REGRESSÃO LINEAR

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    • ABNT

      CORDEIRO, Gauss Moutinho et al. The Kumaraswamy normal linear regression model with applications. Communications in Statistics - Simulation and Computation, v. 47, p. 3062-3082, 2018Tradução . . Disponível em: https://doi.org/10.1080/03610918.2017.1367808. Acesso em: 05 jul. 2025.

    • APA

      Cordeiro, G. M., Machado, E. C., Botter, D. A., & Sandoval, M. C. (2018). The Kumaraswamy normal linear regression model with applications. Communications in Statistics - Simulation and Computation, 47, 3062-3082. doi:10.1080/03610918.2017.1367808

    • NLM

      Cordeiro GM, Machado EC, Botter DA, Sandoval MC. The Kumaraswamy normal linear regression model with applications [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 47 3062-3082.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2017.1367808

    • Vancouver

      Cordeiro GM, Machado EC, Botter DA, Sandoval MC. The Kumaraswamy normal linear regression model with applications [Internet]. Communications in Statistics - Simulation and Computation. 2018 ; 47 3062-3082.[citado 2025 jul. 05 ] Available from: https://doi.org/10.1080/03610918.2017.1367808
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