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Artigo de periodico
Ultrastructural calibration model for proficiency testing (2023)
Aoki, Reiko ; Leão, Dorival; Bustamante, Juan Pablo Mamani; Vilca, Filidor
Source: Journal of Applied Statistics. Unidades: ICMC, INTER: ICMC -UFSCAR
Subjects: TEORIA ASSINTÓTICA, EDUÇÃO DE HIPÓTESES, LABORATÓRIOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
AOKI, Reiko et al. Ultrastructural calibration model for proficiency testing. Journal of Applied Statistics, v. 50, n. 5, p. 1037-1059, 2023Tradução . . Disponível em: https://doi.org/10.1080/02664763.2021.2012563. Acesso em: 12 ago. 2024.
APA
Aoki, R., Leão, D., Bustamante, J. P. M., & Vilca, F. (2023). Ultrastructural calibration model for proficiency testing. Journal of Applied Statistics, 50( 5), 1037-1059. doi:10.1080/02664763.2021.2012563
NLM
Aoki R, Leão D, Bustamante JPM, Vilca F. Ultrastructural calibration model for proficiency testing [Internet]. Journal of Applied Statistics. 2023 ; 50( 5): 1037-1059.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2021.2012563
Vancouver
Aoki R, Leão D, Bustamante JPM, Vilca F. Ultrastructural calibration model for proficiency testing [Internet]. Journal of Applied Statistics. 2023 ; 50( 5): 1037-1059.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2021.2012563
Artigo de periodico
The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil (2023)
Hashimoto, Elisabeth Mie ; Ortega, Edwin Moiséis Marcos ; Cordeiro, Gauss Moutinho ; Cancho, Vicente Garibay ; Silva, I
Source: Journal of Applied Statistics. Unidades: ESALQ, ICMC
Subjects: ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, COVID-19, DADOS CENSURADOS, MODELOS MATEMÁTICOS, SISTEMA ÚNICO DE SAÚDE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HASHIMOTO, Elisabeth Mie et al. The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil. Journal of Applied Statistics, v. 50, n. 8, p. 1665-1685, 2023Tradução . . Disponível em: https://doi.org/10.1080/02664763.2022.2036707. Acesso em: 12 ago. 2024.
APA
Hashimoto, E. M., Ortega, E. M. M., Cordeiro, G. M., Cancho, V. G., & Silva, I. (2023). The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil. Journal of Applied Statistics, 50( 8), 1665-1685. doi:10.1080/02664763.2022.2036707
NLM
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Silva I. The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil [Internet]. Journal of Applied Statistics. 2023 ; 50( 8): 1665-1685.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2022.2036707
Vancouver
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Silva I. The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil [Internet]. Journal of Applied Statistics. 2023 ; 50( 8): 1665-1685.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2022.2036707
Artigo de periodico
Fast inference for robust nonlinear mixed-effects models (2023)
Gomes, Jose Clelto Barros ; Aoki, Reiko ; Lachos, Victor Hugo ; Paula, Gilberto Alvarenga ; Russo, Cibele Maria
Source: Journal of Applied Statistics. Unidades: ICMC, IME
Assunto: MODELOS NÃO LINEARES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GOMES, Jose Clelto Barros et al. Fast inference for robust nonlinear mixed-effects models. Journal of Applied Statistics, v. 50, p. 1568-1591, 2023Tradução . . Disponível em: https://doi.org/10.1080/02664763.2022.2034141. Acesso em: 12 ago. 2024.
APA
Gomes, J. C. B., Aoki, R., Lachos, V. H., Paula, G. A., & Russo, C. M. (2023). Fast inference for robust nonlinear mixed-effects models. Journal of Applied Statistics, 50, 1568-1591. doi:10.1080/02664763.2022.2034141
NLM
Gomes JCB, Aoki R, Lachos VH, Paula GA, Russo CM. Fast inference for robust nonlinear mixed-effects models [Internet]. Journal of Applied Statistics. 2023 ; 50 1568-1591.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2022.2034141
Vancouver
Gomes JCB, Aoki R, Lachos VH, Paula GA, Russo CM. Fast inference for robust nonlinear mixed-effects models [Internet]. Journal of Applied Statistics. 2023 ; 50 1568-1591.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2022.2034141
Artigo de periodico
A hierarchical Bayesian approach for modeling the evolution of the 7-day moving average of the number of deaths by COVID-19 (2023)
Saraiva, Erlandson Ferreira ; Sauer, Leandro ; Pereira, Carlos Alberto de Bragança
Source: Journal of Applied Statistics. Unidade: IME
Subjects: ESTATÍSTICA APLICADA, INFERÊNCIA BAYESIANA, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SARAIVA, Erlandson Ferreira e SAUER, Leandro e PEREIRA, Carlos Alberto de Bragança. A hierarchical Bayesian approach for modeling the evolution of the 7-day moving average of the number of deaths by COVID-19. Journal of Applied Statistics, v. 50, n. 10, p. 2194-2208, 2023Tradução . . Disponível em: https://doi.org/10.1080/02664763.2022.2070136. Acesso em: 12 ago. 2024.
APA
Saraiva, E. F., Sauer, L., & Pereira, C. A. de B. (2023). A hierarchical Bayesian approach for modeling the evolution of the 7-day moving average of the number of deaths by COVID-19. Journal of Applied Statistics, 50( 10), 2194-2208. doi:10.1080/02664763.2022.2070136
NLM
Saraiva EF, Sauer L, Pereira CA de B. A hierarchical Bayesian approach for modeling the evolution of the 7-day moving average of the number of deaths by COVID-19 [Internet]. Journal of Applied Statistics. 2023 ; 50( 10): 2194-2208.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2022.2070136
Vancouver
Saraiva EF, Sauer L, Pereira CA de B. A hierarchical Bayesian approach for modeling the evolution of the 7-day moving average of the number of deaths by COVID-19 [Internet]. Journal of Applied Statistics. 2023 ; 50( 10): 2194-2208.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2022.2070136
Artigo de periodico
A finite mixture mixed proportion regression model for classification problems in longitudinal voting data (2023)
Paz, Rosineide Fernando da ; Bazán Guzmán, Jorge Luis ; Lachos, Victor Hugo ; Dey, Dipak Kumar
Source: Journal of Applied Statistics. Unidade: ICMC
Subjects: INFERÊNCIA BAYESIANA, MÉTODOS MCMC, CLUSTERS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PAZ, Rosineide Fernando da et al. A finite mixture mixed proportion regression model for classification problems in longitudinal voting data. Journal of Applied Statistics, v. 50, n. 4, p. 871-888, 2023Tradução . . Disponível em: https://doi.org/10.1080/02664763.2021.1998392. Acesso em: 12 ago. 2024.
APA
Paz, R. F. da, Bazán Guzmán, J. L., Lachos, V. H., & Dey, D. K. (2023). A finite mixture mixed proportion regression model for classification problems in longitudinal voting data. Journal of Applied Statistics, 50( 4), 871-888. doi:10.1080/02664763.2021.1998392
NLM
Paz RF da, Bazán Guzmán JL, Lachos VH, Dey DK. A finite mixture mixed proportion regression model for classification problems in longitudinal voting data [Internet]. Journal of Applied Statistics. 2023 ; 50( 4): 871-888.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2021.1998392
Vancouver
Paz RF da, Bazán Guzmán JL, Lachos VH, Dey DK. A finite mixture mixed proportion regression model for classification problems in longitudinal voting data [Internet]. Journal of Applied Statistics. 2023 ; 50( 4): 871-888.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2021.1998392
Artigo de periodico
A hierarchical Bayesian analysis for bivariate Weibull distribution under left-censoring scheme (2023)
Peralta, Danielle; Oliveira, Ricardo Puziol de; Achcar, Jorge Alberto
Source: Journal of Applied Statistics. Unidade: FMRP
Subjects: DISTRIBUIÇÕES (PROBABILIDADE), INFERÊNCIA BAYESIANA, DADOS CENSURADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PERALTA, Danielle e OLIVEIRA, Ricardo Puziol de e ACHCAR, Jorge Alberto. A hierarchical Bayesian analysis for bivariate Weibull distribution under left-censoring scheme. Journal of Applied Statistics, v. 51, n. 9, p. 1772-1791, 2023Tradução . . Disponível em: https://doi.org/10.1080/02664763.2023.2235093. Acesso em: 12 ago. 2024.
APA
Peralta, D., Oliveira, R. P. de, & Achcar, J. A. (2023). A hierarchical Bayesian analysis for bivariate Weibull distribution under left-censoring scheme. Journal of Applied Statistics, 51( 9), 1772-1791. doi:10.1080/02664763.2023.2235093
NLM
Peralta D, Oliveira RP de, Achcar JA. A hierarchical Bayesian analysis for bivariate Weibull distribution under left-censoring scheme [Internet]. Journal of Applied Statistics. 2023 ; 51( 9): 1772-1791.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2023.2235093
Vancouver
Peralta D, Oliveira RP de, Achcar JA. A hierarchical Bayesian analysis for bivariate Weibull distribution under left-censoring scheme [Internet]. Journal of Applied Statistics. 2023 ; 51( 9): 1772-1791.[citado 2024 ago. 12 ] Available from: https://doi.org/10.1080/02664763.2023.2235093

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