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)
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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: 14 set. 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:10.1080/00949655.2019.1643345NLM
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 set. 14 ] Available from: https://doi.org/10.1080/00949655.2019.1643345Vancouver
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 set. 14 ] Available from: https://doi.org/10.1080/00949655.2019.1643345
