An integrated approach for making inference on the number of clusters in a mixture model (2021)
- Authors:
- USP affiliated authors: SUZUKI, ADRIANO KAMIMURA - ICMC ; PEREIRA, CARLOS ALBERTO DE BRAGANCA - IME ; MILAN, LUIS APARECIDO - INTER: ICMC -UFSCAR
- Unidades: ICMC; IME; INTER: ICMC -UFSCAR
- Subjects: PROBABILIDADE; PROCESSOS ESTOCÁSTICOS
- Keywords: model-based clustering; mixture model; EM algorithm; integrated approach
- Agências de fomento:
- Language: Inglês
- Imprenta:
-
ABNT
SARAIVA, Erlandson Ferreira et al. An integrated approach for making inference on the number of clusters in a mixture model. Tradução . Basel: MDPI, 2021. . Disponível em: https://www.mdpi.com/1099-4300/22/12/1438/pdf. Acesso em: 17 abr. 2024. -
APA
Saraiva, E. F., Suzuki, A. K., Milan, L. A., & Pereira, C. A. de B. (2021). An integrated approach for making inference on the number of clusters in a mixture model. In . Basel: MDPI. Recuperado de https://www.mdpi.com/1099-4300/22/12/1438/pdf -
NLM
Saraiva EF, Suzuki AK, Milan LA, Pereira CA de B. An integrated approach for making inference on the number of clusters in a mixture model [Internet]. Basel: MDPI; 2021. [citado 2024 abr. 17 ] Available from: https://www.mdpi.com/1099-4300/22/12/1438/pdf -
Vancouver
Saraiva EF, Suzuki AK, Milan LA, Pereira CA de B. An integrated approach for making inference on the number of clusters in a mixture model [Internet]. Basel: MDPI; 2021. [citado 2024 abr. 17 ] Available from: https://www.mdpi.com/1099-4300/22/12/1438/pdf - Uma abordagem bayesiana para o modelo de sobrevivência bivariado derivado da cópula AMH
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