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Artigo de periodico
The generalized odd log-logistic-G regression with interval-censored survival data (2024)
Vigas, Valdemiro Piedade ; Ortega, Edwin Moises Marcos ; Suzuki, Adriano Kamimura ; Cordeiro, Gauss Moutinho ; Santos Junior, Paulo Cerqueira
Fonte: Journal of Applied Statistics. Unidades: ESALQ, ICMC
Assuntos: ANÁLISE DE SOBREVIVÊNCIA, DADOS CENSURADOS, INFERÊNCIA BAYESIANA, REGRESSÃO LOGÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
VIGAS, Valdemiro Piedade et al. The generalized odd log-logistic-G regression with interval-censored survival data. Journal of Applied Statistics, v. 51, n. 9, p. 2024, 2024Tradução . . Disponível em: https://doi.org/10.1080/02664763.2023.2230533. Acesso em: 01 out. 2024.
APA
Vigas, V. P., Ortega, E. M. M., Suzuki, A. K., Cordeiro, G. M., & Santos Junior, P. C. (2024). The generalized odd log-logistic-G regression with interval-censored survival data. Journal of Applied Statistics, 51( 9), 2024. doi:10.1080/02664763.2023.2230533
NLM
Vigas VP, Ortega EMM, Suzuki AK, Cordeiro GM, Santos Junior PC. The generalized odd log-logistic-G regression with interval-censored survival data [Internet]. Journal of Applied Statistics. 2024 ; 51( 9): 2024.[citado 2024 out. 01 ] Available from: https://doi.org/10.1080/02664763.2023.2230533
Vancouver
Vigas VP, Ortega EMM, Suzuki AK, Cordeiro GM, Santos Junior PC. The generalized odd log-logistic-G regression with interval-censored survival data [Internet]. Journal of Applied Statistics. 2024 ; 51( 9): 2024.[citado 2024 out. 01 ] Available from: https://doi.org/10.1080/02664763.2023.2230533
Artigo de periodico
On three-parameter exponential distribution: properties, bayesian and non-bayesian estimation based on complete and censored samples (2021)
Afify, Ahmed Z ; Suzuki, Adriano Kamimura ; Zang, Chunfang ; Nassar, Mazen
Fonte: Communications in Statistics : Simulation and Computation. Unidade: ICMC
Assuntos: ANÁLISE DE DADOS, CADEIAS DE MARKOV, ESTIMADOR DE BAYES EMPÍRICO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
AFIFY, Ahmed Z et al. On three-parameter exponential distribution: properties, bayesian and non-bayesian estimation based on complete and censored samples. Communications in Statistics : Simulation and Computation, v. 50, n. 11, p. 3799-3819, 2021Tradução . . Disponível em: https://doi.org/10.1080/03610918.2019.1636995. Acesso em: 01 out. 2024.
APA
Afify, A. Z., Suzuki, A. K., Zang, C., & Nassar, M. (2021). On three-parameter exponential distribution: properties, bayesian and non-bayesian estimation based on complete and censored samples. Communications in Statistics : Simulation and Computation, 50( 11), 3799-3819. doi:10.1080/03610918.2019.1636995
NLM
Afify AZ, Suzuki AK, Zang C, Nassar M. On three-parameter exponential distribution: properties, bayesian and non-bayesian estimation based on complete and censored samples [Internet]. Communications in Statistics : Simulation and Computation. 2021 ; 50( 11): 3799-3819.[citado 2024 out. 01 ] Available from: https://doi.org/10.1080/03610918.2019.1636995
Vancouver
Afify AZ, Suzuki AK, Zang C, Nassar M. On three-parameter exponential distribution: properties, bayesian and non-bayesian estimation based on complete and censored samples [Internet]. Communications in Statistics : Simulation and Computation. 2021 ; 50( 11): 3799-3819.[citado 2024 out. 01 ] Available from: https://doi.org/10.1080/03610918.2019.1636995
Artigo de periodico
Bayesian analysis of Birnbaum-Saunders survival model with cure fraction under a variety of activation mechanism (2020)
Barriga, Gladys Dorotea Cacsire ; Dey, Dipak Kumar ; Cancho, Vicente Garibay ; Suzuki, Adriano Kamimura
Fonte: Model Assisted Statistics and Applications. Unidade: ICMC
Assuntos: ANÁLISE DE SOBREVIVÊNCIA, DISTRIBUIÇÕES (PROBABILIDADE), MÉTODOS MCMC, INFERÊNCIA BAYESIANA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARRIGA, Gladys Dorotea Cacsire et al. Bayesian analysis of Birnbaum-Saunders survival model with cure fraction under a variety of activation mechanism. Model Assisted Statistics and Applications, n. 1, p. 35-51, 2020Tradução . . Disponível em: https://doi.org/10.3233/MAS-190477. Acesso em: 01 out. 2024.
APA
Barriga, G. D. C., Dey, D. K., Cancho, V. G., & Suzuki, A. K. (2020). Bayesian analysis of Birnbaum-Saunders survival model with cure fraction under a variety of activation mechanism. Model Assisted Statistics and Applications, ( 1), 35-51. doi:10.3233/MAS-190477
NLM
Barriga GDC, Dey DK, Cancho VG, Suzuki AK. Bayesian analysis of Birnbaum-Saunders survival model with cure fraction under a variety of activation mechanism [Internet]. Model Assisted Statistics and Applications. 2020 ;( 1): 35-51.[citado 2024 out. 01 ] Available from: https://doi.org/10.3233/MAS-190477
Vancouver
Barriga GDC, Dey DK, Cancho VG, Suzuki AK. Bayesian analysis of Birnbaum-Saunders survival model with cure fraction under a variety of activation mechanism [Internet]. Model Assisted Statistics and Applications. 2020 ;( 1): 35-51.[citado 2024 out. 01 ] Available from: https://doi.org/10.3233/MAS-190477
Artigo de periodico
The Spike-and-Slab Lasso regression modeling with compositional covariates: an application on Brazilian children malnutrition data (2020)
Louzada, Francisco ; Shimizu, Taciana Kisaki Oliveira; Suzuki, Adriano Kamimura
Fonte: Statistical Methods in Medical Research. Unidades: ICMC, INTER: ICMC -UFSCAR
Assuntos: ANÁLISE DE SOBREVIVÊNCIA, ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LOUZADA, Francisco e SHIMIZU, Taciana Kisaki Oliveira e SUZUKI, Adriano Kamimura. The Spike-and-Slab Lasso regression modeling with compositional covariates: an application on Brazilian children malnutrition data. Statistical Methods in Medical Research, v. 29, n. 5, p. 1434-1446, 2020Tradução . . Disponível em: https://doi.org/10.1177/0962280219863817. Acesso em: 01 out. 2024.
APA
Louzada, F., Shimizu, T. K. O., & Suzuki, A. K. (2020). The Spike-and-Slab Lasso regression modeling with compositional covariates: an application on Brazilian children malnutrition data. Statistical Methods in Medical Research, 29( 5), 1434-1446. doi:10.1177/0962280219863817
NLM
Louzada F, Shimizu TKO, Suzuki AK. The Spike-and-Slab Lasso regression modeling with compositional covariates: an application on Brazilian children malnutrition data [Internet]. Statistical Methods in Medical Research. 2020 ; 29( 5): 1434-1446.[citado 2024 out. 01 ] Available from: https://doi.org/10.1177/0962280219863817
Vancouver
Louzada F, Shimizu TKO, Suzuki AK. The Spike-and-Slab Lasso regression modeling with compositional covariates: an application on Brazilian children malnutrition data [Internet]. Statistical Methods in Medical Research. 2020 ; 29( 5): 1434-1446.[citado 2024 out. 01 ] Available from: https://doi.org/10.1177/0962280219863817
Artigo de periodico
A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling (2019)
Saraiva, Erlandson Ferreira ; Pereira, C. A. B; Suzuki, Adriano Kamimura
Fonte: Journal of Statistical Computation and Simulation. Unidade: ICMC
Assuntos: CLUSTERS, ALGORITMOS ÚTEIS E ESPECÍFICOS, DISTRIBUIÇÕES (PROBABILIDADE)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 01 out. 2024.
APA
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 2024 out. 01 ] 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 2024 out. 01 ] Available from: https://doi.org/10.1080/00949655.2019.1643345

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