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Artigo de periodico
A new family of quantile regression models applied to nutritional data (2024)
Olmos, Isaac Esteban Cortés ; Castro, Mário de ; Mateluna, Diego Ignacio Gallardo
Source: Journal of Applied Statistics. Unidades: ICMC, INTER: ICMC -UFSCAR
Subjects: ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, DISTRIBUIÇÕES (PROBABILIDADE), VEROSSIMILHANÇA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLMOS, Isaac Esteban Cortés e CASTRO, Mário de e MATELUNA, Diego Ignacio Gallardo. A new family of quantile regression models applied to nutritional data. Journal of Applied Statistics, v. 51, n. 7, p. 1378-1398, 2024Tradução . . Disponível em: https://doi.org/10.1080/02664763.2023.2203882. Acesso em: 17 jul. 2024.
APA
Olmos, I. E. C., Castro, M. de, & Mateluna, D. I. G. (2024). A new family of quantile regression models applied to nutritional data. Journal of Applied Statistics, 51( 7), 1378-1398. doi:10.1080/02664763.2023.2203882
NLM
Olmos IEC, Castro M de, Mateluna DIG. A new family of quantile regression models applied to nutritional data [Internet]. Journal of Applied Statistics. 2024 ; 51( 7): 1378-1398.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664763.2023.2203882
Vancouver
Olmos IEC, Castro M de, Mateluna DIG. A new family of quantile regression models applied to nutritional data [Internet]. Journal of Applied Statistics. 2024 ; 51( 7): 1378-1398.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664763.2023.2203882
Artigo de periodico
The Rayleigh–Lindley model: properties and applications (2019)
Gómez, Yolanda M; Gallardo, Diego I; Iriarte, Yuri; Bolfarine, Heleno
Source: Journal of Applied Statistics. Unidade: IME
Assunto: ESTATÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GÓMEZ, Yolanda M et al. The Rayleigh–Lindley model: properties and applications. Journal of Applied Statistics, v. 46, n. 1, p. 141-163, 2019Tradução . . Disponível em: https://doi.org/10.1080/02664763.2018.1458825. Acesso em: 17 jul. 2024.
APA
Gómez, Y. M., Gallardo, D. I., Iriarte, Y., & Bolfarine, H. (2019). The Rayleigh–Lindley model: properties and applications. Journal of Applied Statistics, 46( 1), 141-163. doi:10.1080/02664763.2018.1458825
NLM
Gómez YM, Gallardo DI, Iriarte Y, Bolfarine H. The Rayleigh–Lindley model: properties and applications [Internet]. Journal of Applied Statistics. 2019 ; 46( 1): 141-163.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664763.2018.1458825
Vancouver
Gómez YM, Gallardo DI, Iriarte Y, Bolfarine H. The Rayleigh–Lindley model: properties and applications [Internet]. Journal of Applied Statistics. 2019 ; 46( 1): 141-163.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664763.2018.1458825
Artigo de periodico
Sensitivity analysis of longitudinal count responses: a local influence approach and application to medical data (2019)
Silva, Alejandra Andrea Tapia ; Giampaoli, Viviana ; Diaz, Maria del Pilar ; Leiva-Sanchez, Victor
Source: Journal of Applied Statistics. Unidade: IME
Subjects: MÉTODO DE MONTE CARLO, PROCESSOS DE POISSON, BIOESTATÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Alejandra Andrea Tapia et al. Sensitivity analysis of longitudinal count responses: a local influence approach and application to medical data. Journal of Applied Statistics, v. 46, n. 6, p. 1021-1042, 2019Tradução . . Disponível em: https://doi.org/10.1080/02664763.2018.1531978. Acesso em: 17 jul. 2024.
APA
Silva, A. A. T., Giampaoli, V., Diaz, M. del P., & Leiva-Sanchez, V. (2019). Sensitivity analysis of longitudinal count responses: a local influence approach and application to medical data. Journal of Applied Statistics, 46( 6), 1021-1042. doi:10.1080/02664763.2018.1531978
NLM
Silva AAT, Giampaoli V, Diaz M del P, Leiva-Sanchez V. Sensitivity analysis of longitudinal count responses: a local influence approach and application to medical data [Internet]. Journal of Applied Statistics. 2019 ; 46( 6): 1021-1042.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664763.2018.1531978
Vancouver
Silva AAT, Giampaoli V, Diaz M del P, Leiva-Sanchez V. Sensitivity analysis of longitudinal count responses: a local influence approach and application to medical data [Internet]. Journal of Applied Statistics. 2019 ; 46( 6): 1021-1042.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664763.2018.1531978
Artigo de periodico
A new cure rate model based on the Yule–Simon distribution with application to a melanoma data set (2017)
Gallardo Mateluna, Diego Ignacio; Gómez, Héctor W; Bolfarine, Heleno
Source: Journal of Applied Statistics. Unidade: IME
Subjects: INFERÊNCIA ESTATÍSTICA, ESTATÍSTICA APLICADA, MELANOMA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GALLARDO MATELUNA, Diego Ignacio e GÓMEZ, Héctor W e BOLFARINE, Heleno. A new cure rate model based on the Yule–Simon distribution with application to a melanoma data set. Journal of Applied Statistics, v. 44, n. 7, p. 1153-1164, 2017Tradução . . Disponível em: https://doi.org/10.1080/02664763.2016.1194385. Acesso em: 17 jul. 2024.
APA
Gallardo Mateluna, D. I., Gómez, H. W., & Bolfarine, H. (2017). A new cure rate model based on the Yule–Simon distribution with application to a melanoma data set. Journal of Applied Statistics, 44( 7), 1153-1164. doi:10.1080/02664763.2016.1194385
NLM
Gallardo Mateluna DI, Gómez HW, Bolfarine H. A new cure rate model based on the Yule–Simon distribution with application to a melanoma data set [Internet]. Journal of Applied Statistics. 2017 ; 44( 7): 1153-1164.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664763.2016.1194385
Vancouver
Gallardo Mateluna DI, Gómez HW, Bolfarine H. A new cure rate model based on the Yule–Simon distribution with application to a melanoma data set [Internet]. Journal of Applied Statistics. 2017 ; 44( 7): 1153-1164.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664763.2016.1194385
Artigo de periodico
Bayesian inference for skew-normal linear mixed models (2007)
Arellano-Valle, Reinaldo Boris ; Bolfarine, Heleno ; Lachos, Victor Hugo
Source: Journal of Applied Statistics. Unidade: IME
Subjects: INFERÊNCIA BAYESIANA, ANÁLISE MULTIVARIADA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ARELLANO-VALLE, Reinaldo Boris e BOLFARINE, Heleno e LACHOS, Victor Hugo. Bayesian inference for skew-normal linear mixed models. Journal of Applied Statistics, v. 34, n. 6, p. 663-682, 2007Tradução . . Disponível em: https://doi.org/10.1080/02664760701236905. Acesso em: 17 jul. 2024.
APA
Arellano-Valle, R. B., Bolfarine, H., & Lachos, V. H. (2007). Bayesian inference for skew-normal linear mixed models. Journal of Applied Statistics, 34( 6), 663-682. doi:10.1080/02664760701236905
NLM
Arellano-Valle RB, Bolfarine H, Lachos VH. Bayesian inference for skew-normal linear mixed models [Internet]. Journal of Applied Statistics. 2007 ; 34( 6): 663-682.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664760701236905
Vancouver
Arellano-Valle RB, Bolfarine H, Lachos VH. Bayesian inference for skew-normal linear mixed models [Internet]. Journal of Applied Statistics. 2007 ; 34( 6): 663-682.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1080/02664760701236905

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