A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GONG, Ruobin et al. Learning and total evidence with imprecise probabilities. International Journal of Approximate Reasoning, v. 151, p. 21-32, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2022.08.016. Acesso em: 07 set. 2024.
APA
Gong, R., Kadane, J. B., Schervish, M. J., Seidenfeld, T., & Stern, R. B. (2022). Learning and total evidence with imprecise probabilities. International Journal of Approximate Reasoning, 151, 21-32. doi:10.1016/j.ijar.2022.08.016
NLM
Gong R, Kadane JB, Schervish MJ, Seidenfeld T, Stern RB. Learning and total evidence with imprecise probabilities [Internet]. International Journal of Approximate Reasoning. 2022 ; 151 21-32.[citado 2024 set. 07 ] Available from: https://doi.org/10.1016/j.ijar.2022.08.016
Vancouver
Gong R, Kadane JB, Schervish MJ, Seidenfeld T, Stern RB. Learning and total evidence with imprecise probabilities [Internet]. International Journal of Approximate Reasoning. 2022 ; 151 21-32.[citado 2024 set. 07 ] Available from: https://doi.org/10.1016/j.ijar.2022.08.016
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FUJITA, André et al. A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data. Statistics in Medicine, v. 33, n. 28, p. 4949-4962, 2014Tradução . . Disponível em: https://doi.org/10.1002/sim.6292. Acesso em: 07 set. 2024.
APA
Fujita, A., Takahashi, D. Y., Patriota, A. G., & Sato, J. R. (2014). A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data. Statistics in Medicine, 33( 28), 4949-4962. doi:10.1002/sim.6292
NLM
Fujita A, Takahashi DY, Patriota AG, Sato JR. A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data [Internet]. Statistics in Medicine. 2014 ; 33( 28): 4949-4962.[citado 2024 set. 07 ] Available from: https://doi.org/10.1002/sim.6292
Vancouver
Fujita A, Takahashi DY, Patriota AG, Sato JR. A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data [Internet]. Statistics in Medicine. 2014 ; 33( 28): 4949-4962.[citado 2024 set. 07 ] Available from: https://doi.org/10.1002/sim.6292
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CASSANDRO, Marzio et al. A stochastic model for the speech sonority. Mathématiques & sciences humaines., n. 180, p. 43-55, 2007Tradução . . Disponível em: https://doi.org/10.4000/msh.7653. Acesso em: 07 set. 2024.
APA
Cassandro, M., Collet, P., Duarte, D., Galves, A., & Garcia, J. E. (2007). A stochastic model for the speech sonority. Mathématiques & sciences humaines., ( 180), 43-55. doi:10.4000/msh.7653
NLM
Cassandro M, Collet P, Duarte D, Galves A, Garcia JE. A stochastic model for the speech sonority [Internet]. Mathématiques & sciences humaines. 2007 ;( 180): 43-55.[citado 2024 set. 07 ] Available from: https://doi.org/10.4000/msh.7653
Vancouver
Cassandro M, Collet P, Duarte D, Galves A, Garcia JE. A stochastic model for the speech sonority [Internet]. Mathématiques & sciences humaines. 2007 ;( 180): 43-55.[citado 2024 set. 07 ] Available from: https://doi.org/10.4000/msh.7653