Fonte: Computers. Unidades: FEA, ESALQ, EP
Assuntos: REGRESSÃO LINEAR, DISTRIBUIÇÃO DISCRETA, PYTHON, ANÁLISE ESTATÍSTICA DE DADOS
ABNT
FÁVERO, Luiz Paulo Lopes e DUARTE, Alexandre e SANTOS, Helder Prado. A new computational algorithm for assessing overdispersion and zero-inflation in machine learning count models with Python. Computers, v. 13, n. 4, p. 1-15, 2024Tradução . . Disponível em: https://www.mdpi.com/2073-431X/13/4/88. Acesso em: 17 ago. 2024.APA
Fávero, L. P. L., Duarte, A., & Santos, H. P. (2024). A new computational algorithm for assessing overdispersion and zero-inflation in machine learning count models with Python. Computers, 13( 4), 1-15. doi:10.3390/computers13040088NLM
Fávero LPL, Duarte A, Santos HP. A new computational algorithm for assessing overdispersion and zero-inflation in machine learning count models with Python [Internet]. Computers. 2024 ; 13( 4): 1-15.[citado 2024 ago. 17 ] Available from: https://www.mdpi.com/2073-431X/13/4/88Vancouver
Fávero LPL, Duarte A, Santos HP. A new computational algorithm for assessing overdispersion and zero-inflation in machine learning count models with Python [Internet]. Computers. 2024 ; 13( 4): 1-15.[citado 2024 ago. 17 ] Available from: https://www.mdpi.com/2073-431X/13/4/88