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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: 16 nov. 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 nov. 16 ] 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 nov. 16 ] Available from: https://doi.org/10.1080/02664763.2021.1998392
Artigo de periodico
Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions (2014)
Fioruci, José Augusto; Ehlers, Ricardo Sandes ; Andrade, Marinho Gomes de
Source: Journal of Applied Statistics. Unidade: ICMC
Subjects: INFERÊNCIA BAYESIANA, INFERÊNCIA PARAMÉTRICA, ANÁLISE MULTIVARIADA, MÉTODOS MCMC
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FIORUCI, José Augusto e EHLERS, Ricardo Sandes e ANDRADE, Marinho Gomes de. Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions. Journal of Applied Statistics, v. 41, n. 2, p. 320-331, 2014Tradução . . Disponível em: https://doi.org/10.1080/02664763.2013.839635. Acesso em: 16 nov. 2025.
APA
Fioruci, J. A., Ehlers, R. S., & Andrade, M. G. de. (2014). Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions. Journal of Applied Statistics, 41( 2), 320-331. doi:10.1080/02664763.2013.839635
NLM
Fioruci JA, Ehlers RS, Andrade MG de. Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions [Internet]. Journal of Applied Statistics. 2014 ; 41( 2): 320-331.[citado 2025 nov. 16 ] Available from: https://doi.org/10.1080/02664763.2013.839635
Vancouver
Fioruci JA, Ehlers RS, Andrade MG de. Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions [Internet]. Journal of Applied Statistics. 2014 ; 41( 2): 320-331.[citado 2025 nov. 16 ] Available from: https://doi.org/10.1080/02664763.2013.839635
Artigo de periodico
Dynamic functional data analysis with non-parametric state space models (2014)
Laurini, Marcio Poletti
Source: Journal of Applied Statistics. Unidade: FEARP
Subjects: DINÂMICA DAS ESTRUTURAS, MÉTODOS MCMC, INFERÊNCIA BAYESIANA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LAURINI, Marcio Poletti. Dynamic functional data analysis with non-parametric state space models. Journal of Applied Statistics, v. 41, n. 1, p. 142-163, 2014Tradução . . Disponível em: https://doi.org/10.1080/02664763.2013.838663. Acesso em: 16 nov. 2025.
APA
Laurini, M. P. (2014). Dynamic functional data analysis with non-parametric state space models. Journal of Applied Statistics, 41( 1), 142-163. doi:10.1080/02664763.2013.838663
NLM
Laurini MP. Dynamic functional data analysis with non-parametric state space models [Internet]. Journal of Applied Statistics. 2014 ; 41( 1): 142-163.[citado 2025 nov. 16 ] Available from: https://doi.org/10.1080/02664763.2013.838663
Vancouver
Laurini MP. Dynamic functional data analysis with non-parametric state space models [Internet]. Journal of Applied Statistics. 2014 ; 41( 1): 142-163.[citado 2025 nov. 16 ] Available from: https://doi.org/10.1080/02664763.2013.838663
Artigo de periodico
A multiple group item response theory model with centered skew-normal latent trait distributions under a Bayesian framework (2013)
Santos, Jose R.S.; Azevedo, Caio Lucidius Naberezny ; Bolfarine, Heleno
Source: Journal of Applied Statistics. Unidade: IME
Subjects: TEORIA DE RESPOSTA AO ITEM, DISTRIBUIÇÃO NORMAL, INFERÊNCIA BAYESIANA, MÉTODOS MCMC
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Jose R.S. e AZEVEDO, Caio Lucidius Naberezny e BOLFARINE, Heleno. A multiple group item response theory model with centered skew-normal latent trait distributions under a Bayesian framework. Journal of Applied Statistics, v. 40, n. 10, p. 2129-2149, 2013Tradução . . Disponível em: https://doi.org/10.1080/02664763.2013.807331. Acesso em: 16 nov. 2025.
APA
Santos, J. R. S., Azevedo, C. L. N., & Bolfarine, H. (2013). A multiple group item response theory model with centered skew-normal latent trait distributions under a Bayesian framework. Journal of Applied Statistics, 40( 10), 2129-2149. doi:10.1080/02664763.2013.807331
NLM
Santos JRS, Azevedo CLN, Bolfarine H. A multiple group item response theory model with centered skew-normal latent trait distributions under a Bayesian framework [Internet]. Journal of Applied Statistics. 2013 ; 40( 10): 2129-2149.[citado 2025 nov. 16 ] Available from: https://doi.org/10.1080/02664763.2013.807331
Vancouver
Santos JRS, Azevedo CLN, Bolfarine H. A multiple group item response theory model with centered skew-normal latent trait distributions under a Bayesian framework [Internet]. Journal of Applied Statistics. 2013 ; 40( 10): 2129-2149.[citado 2025 nov. 16 ] Available from: https://doi.org/10.1080/02664763.2013.807331

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