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Filtros : "Financiamento FAPESP" "Indexado no MathSciNet" "Lachos, Victor Hugo" Limpar

Filtros

Artigo de periodico
Penalized complexity priors for the skewness parameter of power links (2024)
Ordoñez, Jose A ; Prates, Marcos Oliveira ; Bazán Guzmán, Jorge Luis ; Lachos, Victor Hugo
Source: Canadian Journal of Statistics. Unidade: ICMC
Subjects: DISTRIBUIÇÃO T, SIMULAÇÃO (ESTATÍSTICA), INFERÊNCIA BAYESIANA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ORDOÑEZ, Jose A et al. Penalized complexity priors for the skewness parameter of power links. Canadian Journal of Statistics, v. 52, n. 1, p. 98-117, 2024Tradução . . Disponível em: https://doi.org/10.1002/cjs.11769. Acesso em: 08 out. 2025.
APA
Ordoñez, J. A., Prates, M. O., Bazán Guzmán, J. L., & Lachos, V. H. (2024). Penalized complexity priors for the skewness parameter of power links. Canadian Journal of Statistics, 52( 1), 98-117. doi:10.1002/cjs.11769
NLM
Ordoñez JA, Prates MO, Bazán Guzmán JL, Lachos VH. Penalized complexity priors for the skewness parameter of power links [Internet]. Canadian Journal of Statistics. 2024 ; 52( 1): 98-117.[citado 2025 out. 08 ] Available from: https://doi.org/10.1002/cjs.11769
Vancouver
Ordoñez JA, Prates MO, Bazán Guzmán JL, Lachos VH. Penalized complexity priors for the skewness parameter of power links [Internet]. Canadian Journal of Statistics. 2024 ; 52( 1): 98-117.[citado 2025 out. 08 ] Available from: https://doi.org/10.1002/cjs.11769
Artigo de periodico
A finite mixture mixed proportion regression model for classification problems in longitudinal voting data (2023)
Paz, Rosineide Fernando da ; Bazán Guzmán, Jorge Luis ; Lachos, Victor Hugo ; Dey, Dipak Kumar
Source: Journal of Applied Statistics. Unidade: ICMC
Subjects: INFERÊNCIA BAYESIANA, MÉTODOS MCMC, CLUSTERS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PAZ, Rosineide Fernando da et al. A finite mixture mixed proportion regression model for classification problems in longitudinal voting data. Journal of Applied Statistics, v. 50, n. 4, p. 871-888, 2023Tradução . . Disponível em: https://doi.org/10.1080/02664763.2021.1998392. Acesso em: 08 out. 2025.
APA
Paz, R. F. da, Bazán Guzmán, J. L., Lachos, V. H., & Dey, D. K. (2023). A finite mixture mixed proportion regression model for classification problems in longitudinal voting data. Journal of Applied Statistics, 50( 4), 871-888. doi:10.1080/02664763.2021.1998392
NLM
Paz RF da, Bazán Guzmán JL, Lachos VH, Dey DK. A finite mixture mixed proportion regression model for classification problems in longitudinal voting data [Internet]. Journal of Applied Statistics. 2023 ; 50( 4): 871-888.[citado 2025 out. 08 ] Available from: https://doi.org/10.1080/02664763.2021.1998392
Vancouver
Paz RF da, Bazán Guzmán JL, Lachos VH, Dey DK. A finite mixture mixed proportion regression model for classification problems in longitudinal voting data [Internet]. Journal of Applied Statistics. 2023 ; 50( 4): 871-888.[citado 2025 out. 08 ] Available from: https://doi.org/10.1080/02664763.2021.1998392

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