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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
Source: Journal of Statistical Computation and Simulation. Unidade: ICMC
Subjects: 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: 16 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. 16 ] 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. 16 ] Available from: https://doi.org/10.1080/00949655.2019.1643345
Artigo de periodico
Riemann manifold Langevin methods on stochastic volatility estimation (2017)
Zevallos, Mauricio; Gasco, Loretta; Ehlers, Ricardo Sandes
Source: Communications in Statistics - Simulation and Computation. Unidade: ICMC
Subjects: PROCESSOS ESTOCÁSTICOS, INFERÊNCIA BAYESIANA, INFERÊNCIA ESTATÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ZEVALLOS, Mauricio e GASCO, Loretta e EHLERS, Ricardo Sandes. Riemann manifold Langevin methods on stochastic volatility estimation. Communications in Statistics - Simulation and Computation, v. 46, n. 10, p. 7942-7956, 2017Tradução . . Disponível em: https://doi.org/10.1080/03610918.2016.1255972. Acesso em: 16 out. 2024.
APA
Zevallos, M., Gasco, L., & Ehlers, R. S. (2017). Riemann manifold Langevin methods on stochastic volatility estimation. Communications in Statistics - Simulation and Computation, 46( 10), 7942-7956. doi:10.1080/03610918.2016.1255972
NLM
Zevallos M, Gasco L, Ehlers RS. Riemann manifold Langevin methods on stochastic volatility estimation [Internet]. Communications in Statistics - Simulation and Computation. 2017 ; 46( 10): 7942-7956.[citado 2024 out. 16 ] Available from: https://doi.org/10.1080/03610918.2016.1255972
Vancouver
Zevallos M, Gasco L, Ehlers RS. Riemann manifold Langevin methods on stochastic volatility estimation [Internet]. Communications in Statistics - Simulation and Computation. 2017 ; 46( 10): 7942-7956.[citado 2024 out. 16 ] Available from: https://doi.org/10.1080/03610918.2016.1255972
Artigo de periodico
Partitioning gene expression data by data-driven Markov chain Monte Carlo (2016)
Saraiva, E. F; Suzuki, Adriano Kamimura ; Louzada, Francisco ; Milan, Luis
Source: Journal of Applied Statistics. Unidade: ICMC
Subjects: PROBABILIDADE, INFERÊNCIA BAYESIANA, INFERÊNCIA PARAMÉTRICA, INFERÊNCIA ESTATÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SARAIVA, E. F et al. Partitioning gene expression data by data-driven Markov chain Monte Carlo. Journal of Applied Statistics, v. 43, n. 6, p. 1155-1173, 2016Tradução . . Disponível em: https://doi.org/10.1080/02664763.2015.1092113. Acesso em: 16 out. 2024.
APA
Saraiva, E. F., Suzuki, A. K., Louzada, F., & Milan, L. (2016). Partitioning gene expression data by data-driven Markov chain Monte Carlo. Journal of Applied Statistics, 43( 6), 1155-1173. doi:10.1080/02664763.2015.1092113
NLM
Saraiva EF, Suzuki AK, Louzada F, Milan L. Partitioning gene expression data by data-driven Markov chain Monte Carlo [Internet]. Journal of Applied Statistics. 2016 ; 43( 6): 1155-1173.[citado 2024 out. 16 ] Available from: https://doi.org/10.1080/02664763.2015.1092113
Vancouver
Saraiva EF, Suzuki AK, Louzada F, Milan L. Partitioning gene expression data by data-driven Markov chain Monte Carlo [Internet]. Journal of Applied Statistics. 2016 ; 43( 6): 1155-1173.[citado 2024 out. 16 ] Available from: https://doi.org/10.1080/02664763.2015.1092113
Artigo de periodico
Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions (2014)
Fioruci, José Augusto; Ehlers, Ricardo Sandes ; Andrade, Marinho Gomes de
Source: Journal of Applied Statistics. Unidade: ICMC
Subjects: INFERÊNCIA BAYESIANA, INFERÊNCIA PARAMÉTRICA, ANÁLISE MULTIVARIADA, MÉTODOS MCMC
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FIORUCI, José Augusto e EHLERS, Ricardo Sandes e ANDRADE, Marinho Gomes de. Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions. Journal of Applied Statistics, v. 41, n. 2, p. 320-331, 2014Tradução . . Disponível em: https://doi.org/10.1080/02664763.2013.839635. Acesso em: 16 out. 2024.
APA
Fioruci, J. A., Ehlers, R. S., & Andrade, M. G. de. (2014). Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions. Journal of Applied Statistics, 41( 2), 320-331. doi:10.1080/02664763.2013.839635
NLM
Fioruci JA, Ehlers RS, Andrade MG de. Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions [Internet]. Journal of Applied Statistics. 2014 ; 41( 2): 320-331.[citado 2024 out. 16 ] Available from: https://doi.org/10.1080/02664763.2013.839635
Vancouver
Fioruci JA, Ehlers RS, Andrade MG de. Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions [Internet]. Journal of Applied Statistics. 2014 ; 41( 2): 320-331.[citado 2024 out. 16 ] Available from: https://doi.org/10.1080/02664763.2013.839635

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