ReP USP - Resultado da busca

Artigo de periodico
Performance of asymmetric links and correction methods for imbalanced data in binary regression (2019)
Huayanay, Alex de la Cruz; Bazán Guzmán, Jorge Luis ; Cancho, Vicente Garibay ; Dey, Dipak K.
Source: Journal of Statistical Computation and Simulation. Unidade: ICMC
Subjects: ANÁLISE DE DADOS, REGRESSÃO LOGÍSTICA, ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), MODELOS LINEARES GENERALIZADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HUAYANAY, Alex de la Cruz et al. Performance of asymmetric links and correction methods for imbalanced data in binary regression. Journal of Statistical Computation and Simulation, v. 89, n. 9, p. 1694-1714, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2019.1593984. Acesso em: 04 jul. 2025.
APA
Huayanay, A. de la C., Bazán Guzmán, J. L., Cancho, V. G., & Dey, D. K. (2019). Performance of asymmetric links and correction methods for imbalanced data in binary regression. Journal of Statistical Computation and Simulation, 89( 9), 1694-1714. doi:10.1080/00949655.2019.1593984
NLM
Huayanay A de la C, Bazán Guzmán JL, Cancho VG, Dey DK. Performance of asymmetric links and correction methods for imbalanced data in binary regression [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 9): 1694-1714.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1593984
Vancouver
Huayanay A de la C, Bazán Guzmán JL, Cancho VG, Dey DK. Performance of asymmetric links and correction methods for imbalanced data in binary regression [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 9): 1694-1714.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1593984
Artigo de periodico
Zero-spiked regression models generated by gamma random variables with application in the resin oil production (2019)
Hashimoto, Elizabeth M; Ortega, Edwin Moises Marcos; Cordeiro, Gauss M; Cancho, Vicente Garibay ; Klauberg, Carine
Source: Journal of Statistical Computation and Simulation. Unidade: ESALQ
Subjects: REGRESSÃO LINEAR, ÓLEOS VEGETAIS, COPAÍBA, RESINAS VEGETAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HASHIMOTO, Elizabeth M et al. Zero-spiked regression models generated by gamma random variables with application in the resin oil production. Journal of Statistical Computation and Simulation, v. 89, n. 1, p. 52-70, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2018.1534116. Acesso em: 04 jul. 2025.
APA
Hashimoto, E. M., Ortega, E. M. M., Cordeiro, G. M., Cancho, V. G., & Klauberg, C. (2019). Zero-spiked regression models generated by gamma random variables with application in the resin oil production. Journal of Statistical Computation and Simulation, 89( 1), 52-70. doi:10.1080/00949655.2018.1534116
NLM
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Klauberg C. Zero-spiked regression models generated by gamma random variables with application in the resin oil production [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 1): 52-70.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2018.1534116
Vancouver
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Klauberg C. Zero-spiked regression models generated by gamma random variables with application in the resin oil production [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 1): 52-70.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2018.1534116
Artigo de periodico
A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling (2019)
Saraiva, Erlandson Ferreira ; Pereira, C. A. B; Suzuki, Adriano Kamimura
Source: Journal of Statistical Computation and Simulation. Unidade: ICMC
Subjects: CLUSTERS, ALGORITMOS ÚTEIS E ESPECÍFICOS, DISTRIBUIÇÕES (PROBABILIDADE)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SARAIVA, Erlandson Ferreira e PEREIRA, C. A. B e SUZUKI, Adriano Kamimura. A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling. Journal of Statistical Computation and Simulation, v. 89, n. 15, p. 2848-2870, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2019.1643345. Acesso em: 04 jul. 2025.
APA
Saraiva, E. F., Pereira, C. A. B., & Suzuki, A. K. (2019). A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling. Journal of Statistical Computation and Simulation, 89( 15), 2848-2870. doi:10.1080/00949655.2019.1643345
NLM
Saraiva EF, Pereira CAB, Suzuki AK. A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 15): 2848-2870.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1643345
Vancouver
Saraiva EF, Pereira CAB, Suzuki AK. A data-driven selection of the number of clusters in the Dirichlet allocation model via Bayesian mixture modelling [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 15): 2848-2870.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1643345
Artigo de periodico
Generalized autoregressive and moving average models: multicollinearity, interpretation and a new modified model (2019)
Esparza Albarracin, Orlando Yesid ; Alencar, Airlane Pereira ; Ho, Linda Lee
Source: Journal of Statistical Computation and Simulation. Unidades: IME, EP
Subjects: ANALISE DE SÉRIES TEMPORAIS, ANALISE DE REGRESSÃO E DE CORRELAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ESPARZA ALBARRACIN, Orlando Yesid e ALENCAR, Airlane Pereira e HO, Linda Lee. Generalized autoregressive and moving average models: multicollinearity, interpretation and a new modified model. Journal of Statistical Computation and Simulation, v. 89, n. 10, p. 1819-1840, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2019.1599892. Acesso em: 04 jul. 2025.
APA
Esparza Albarracin, O. Y., Alencar, A. P., & Ho, L. L. (2019). Generalized autoregressive and moving average models: multicollinearity, interpretation and a new modified model. Journal of Statistical Computation and Simulation, 89( 10), 1819-1840. doi:10.1080/00949655.2019.1599892
NLM
Esparza Albarracin OY, Alencar AP, Ho LL. Generalized autoregressive and moving average models: multicollinearity, interpretation and a new modified model [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 10): 1819-1840.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1599892
Vancouver
Esparza Albarracin OY, Alencar AP, Ho LL. Generalized autoregressive and moving average models: multicollinearity, interpretation and a new modified model [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 10): 1819-1840.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1599892
Artigo de periodico
Zero-spiked regression models generated by gamma random variables with application in the resin oil production (2019)
Hashimoto, Elizabeth Mie; Ortega, Edwin Moisés Marcos; Cordeiro, Gauss Moutinho; Cancho, Vicente Garibay ; Klauberg, Carine
Source: Journal of Statistical Computation and Simulation. Unidades: ESALQ, ICMC
Subjects: INFERÊNCIA ESTATÍSTICA, ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HASHIMOTO, Elizabeth Mie et al. Zero-spiked regression models generated by gamma random variables with application in the resin oil production. Journal of Statistical Computation and Simulation, v. 89, n. 1, p. 52-70, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2018.1534116. Acesso em: 04 jul. 2025.
APA
Hashimoto, E. M., Ortega, E. M. M., Cordeiro, G. M., Cancho, V. G., & Klauberg, C. (2019). Zero-spiked regression models generated by gamma random variables with application in the resin oil production. Journal of Statistical Computation and Simulation, 89( 1), 52-70. doi:10.1080/00949655.2018.1534116
NLM
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Klauberg C. Zero-spiked regression models generated by gamma random variables with application in the resin oil production [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 1): 52-70.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2018.1534116
Vancouver
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Klauberg C. Zero-spiked regression models generated by gamma random variables with application in the resin oil production [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 1): 52-70.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2018.1534116
Artigo de periodico
Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model (2019)
Santos, Daiane de Souza; Cancho, Vicente Garibay ; Rodrigues, Josemar
Source: Journal of Statistical Computation and Simulation. Unidade: ICMC
Subjects: DADOS DE CONTAGEM, TESTES DE HIPÓTESES, DISTRIBUIÇÃO DE POISSON, VEROSSIMILHANÇA, MÉTODO DE MONTE CARLO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Daiane de Souza e CANCHO, Vicente Garibay e RODRIGUES, Josemar. Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model. Journal of Statistical Computation and Simulation, v. 89, n. 5, p. 763-775, 2019Tradução . . Disponível em: https://doi.org/10.1080/00949655.2019.1572144. Acesso em: 04 jul. 2025.
APA
Santos, D. de S., Cancho, V. G., & Rodrigues, J. (2019). Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model. Journal of Statistical Computation and Simulation, 89( 5), 763-775. doi:10.1080/00949655.2019.1572144
NLM
Santos D de S, Cancho VG, Rodrigues J. Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 5): 763-775.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1572144
Vancouver
Santos D de S, Cancho VG, Rodrigues J. Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model [Internet]. Journal of Statistical Computation and Simulation. 2019 ; 89( 5): 763-775.[citado 2025 jul. 04 ] Available from: https://doi.org/10.1080/00949655.2019.1572144

USP Schools

ReP

Bem vindo,

Filtros

Authors

USP affiliated authors

Subjects

Funding Agencies

Indexado em

Non normalized affiliation