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Artigo de periodico
Language rythm model selection by weighted kappa (2010)
Giampaoli, Viviana ; Mandel, Arnaldo
Fonte: Journal of Data Science. Unidade: IME
Assunto: LINGUAGEM DE PROGRAMAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GIAMPAOLI, Viviana e MANDEL, Arnaldo. Language rythm model selection by weighted kappa. Journal of Data Science, v. 8, n. 1, p. 91-99, 2010Tradução . . Disponível em: http://www.jds-online.com/v8-1. Acesso em: 28 nov. 2025.
APA
Giampaoli, V., & Mandel, A. (2010). Language rythm model selection by weighted kappa. Journal of Data Science, 8( 1), 91-99. Recuperado de http://www.jds-online.com/v8-1
NLM
Giampaoli V, Mandel A. Language rythm model selection by weighted kappa [Internet]. Journal of Data Science. 2010 ; 8( 1): 91-99.[citado 2025 nov. 28 ] Available from: http://www.jds-online.com/v8-1
Vancouver
Giampaoli V, Mandel A. Language rythm model selection by weighted kappa [Internet]. Journal of Data Science. 2010 ; 8( 1): 91-99.[citado 2025 nov. 28 ] Available from: http://www.jds-online.com/v8-1
Artigo de periodico
The log-exponentiated-weibull regression models with cure rate: local influence and residual analysis (2009)
Cancho, Vicente Garibay ; Ortega, Edwin Moisés Marcos ; Bolfarine, Heleno
Fonte: Journal of Data Science. Unidades: ICMC, ESALQ, IME
Assuntos: INFERÊNCIA BAYESIANA, REGRESSÃO LINEAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CANCHO, Vicente Garibay e ORTEGA, Edwin Moisés Marcos e BOLFARINE, Heleno. The log-exponentiated-weibull regression models with cure rate: local influence and residual analysis. Journal of Data Science, v. 7, n. 4, p. 433-458, 2009Tradução . . Disponível em: https://jds-online.org/journal/JDS/article/973/info. Acesso em: 28 nov. 2025.
APA
Cancho, V. G., Ortega, E. M. M., & Bolfarine, H. (2009). The log-exponentiated-weibull regression models with cure rate: local influence and residual analysis. Journal of Data Science, 7( 4), 433-458. Recuperado de https://jds-online.org/journal/JDS/article/973/info
NLM
Cancho VG, Ortega EMM, Bolfarine H. The log-exponentiated-weibull regression models with cure rate: local influence and residual analysis [Internet]. Journal of Data Science. 2009 ; 7( 4): 433-458.[citado 2025 nov. 28 ] Available from: https://jds-online.org/journal/JDS/article/973/info
Vancouver
Cancho VG, Ortega EMM, Bolfarine H. The log-exponentiated-weibull regression models with cure rate: local influence and residual analysis [Internet]. Journal of Data Science. 2009 ; 7( 4): 433-458.[citado 2025 nov. 28 ] Available from: https://jds-online.org/journal/JDS/article/973/info
Artigo de periodico
Identifying multi-subject cortical activation in MRI: a frequency domain approach (2008)
Sato, João Ricardo; Chiann, Chang ; Taniguchi, Eduardo Hiromassa; Santos, Emerson Gomes dos; Arantes, Paula Ricci; Mourao, Maria Lucia; Amaro Junior, Edson; Morettin, Pedro Alberto
Fonte: Journal of Data Science. Unidades: IME, FM
Assuntos: CÉREBRO (RADIOGRAFIA), ANÁLISE ESPECTRAL, IMAGEM POR RESSONÂNCIA MAGNÉTICA, HEMODINÂMICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SATO, João Ricardo et al. Identifying multi-subject cortical activation in MRI: a frequency domain approach. Journal of Data Science, v. 6, p. 80-103, 2008Tradução . . Acesso em: 28 nov. 2025.
APA
Sato, J. R., Chiann, C., Taniguchi, E. H., Santos, E. G. dos, Arantes, P. R., Mourao, M. L., et al. (2008). Identifying multi-subject cortical activation in MRI: a frequency domain approach. Journal of Data Science, 6, 80-103.
NLM
Sato JR, Chiann C, Taniguchi EH, Santos EG dos, Arantes PR, Mourao ML, Amaro Junior E, Morettin PA. Identifying multi-subject cortical activation in MRI: a frequency domain approach. Journal of Data Science. 2008 ; 6 80-103.[citado 2025 nov. 28 ]
Vancouver
Sato JR, Chiann C, Taniguchi EH, Santos EG dos, Arantes PR, Mourao ML, Amaro Junior E, Morettin PA. Identifying multi-subject cortical activation in MRI: a frequency domain approach. Journal of Data Science. 2008 ; 6 80-103.[citado 2025 nov. 28 ]
Artigo de periodico
Bayesian and Classical Solutions for Binomial Cytogenetic Dosimetry Problem (2003)
Branco, Marcia D'Elia ; Bolfarine, Heleno ; Zuazola, Pilar Loreto Iglesias; Arellano-Valle, Reinaldo Boris
Fonte: Journal of Data Science. Unidade: IME
Assunto: PROCESSOS ESTOCÁSTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BRANCO, Marcia D'Elia et al. Bayesian and Classical Solutions for Binomial Cytogenetic Dosimetry Problem. Journal of Data Science, v. 1, p. 65-82, 2003Tradução . . Disponível em: http://www.jds-online.com/file_download/7/JDS-112.pdf. Acesso em: 28 nov. 2025.
APA
Branco, M. D. 'E., Bolfarine, H., Zuazola, P. L. I., & Arellano-Valle, R. B. (2003). Bayesian and Classical Solutions for Binomial Cytogenetic Dosimetry Problem. Journal of Data Science, 1, 65-82. Recuperado de http://www.jds-online.com/file_download/7/JDS-112.pdf
NLM
Branco MD'E, Bolfarine H, Zuazola PLI, Arellano-Valle RB. Bayesian and Classical Solutions for Binomial Cytogenetic Dosimetry Problem [Internet]. Journal of Data Science. 2003 ; 1 65-82.[citado 2025 nov. 28 ] Available from: http://www.jds-online.com/file_download/7/JDS-112.pdf
Vancouver
Branco MD'E, Bolfarine H, Zuazola PLI, Arellano-Valle RB. Bayesian and Classical Solutions for Binomial Cytogenetic Dosimetry Problem [Internet]. Journal of Data Science. 2003 ; 1 65-82.[citado 2025 nov. 28 ] Available from: http://www.jds-online.com/file_download/7/JDS-112.pdf

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