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An integrated approach for making inference on the number of clusters in a mixture model (2021)
Saraiva, Erlandson Ferreira ; Suzuki, Adriano Kamimura ; Milan, Luis Aparecido ; Pereira, Carlos Alberto de Bragança
Unidades: ICMC, IME, INTER: ICMC -UFSCAR
Subjects: PROBABILIDADE, PROCESSOS ESTOCÁSTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SARAIVA, Erlandson Ferreira et al. An integrated approach for making inference on the number of clusters in a mixture model. Tradução . Basel: MDPI, 2021. . Disponível em: https://www.mdpi.com/1099-4300/22/12/1438/pdf. Acesso em: 28 ago. 2024.
APA
Saraiva, E. F., Suzuki, A. K., Milan, L. A., & Pereira, C. A. de B. (2021). An integrated approach for making inference on the number of clusters in a mixture model. In . Basel: MDPI. Recuperado de https://www.mdpi.com/1099-4300/22/12/1438/pdf
NLM
Saraiva EF, Suzuki AK, Milan LA, Pereira CA de B. An integrated approach for making inference on the number of clusters in a mixture model [Internet]. Basel: MDPI; 2021. [citado 2024 ago. 28 ] Available from: https://www.mdpi.com/1099-4300/22/12/1438/pdf
Vancouver
Saraiva EF, Suzuki AK, Milan LA, Pereira CA de B. An integrated approach for making inference on the number of clusters in a mixture model [Internet]. Basel: MDPI; 2021. [citado 2024 ago. 28 ] Available from: https://www.mdpi.com/1099-4300/22/12/1438/pdf
Artigo de periodico
Bayesian criterion for identification of differentially expressed genes (2021)
Saraiva, Erlandson F ; Milan, Luis Aparecido ; Pereira, Carlos Alberto de Bragança
Source: Communications in Statistics: Case Studies, Data Analysis and Applications. Unidade: IME
Subjects: INFERÊNCIA BAYESIANA, EXPRESSÃO GÊNICA
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ABNT
SARAIVA, Erlandson F e MILAN, Luis Aparecido e PEREIRA, Carlos Alberto de Bragança. Bayesian criterion for identification of differentially expressed genes. Communications in Statistics: Case Studies, Data Analysis and Applications, v. 7, n. 1, p. 1-14, 2021Tradução . . Disponível em: https://doi.org/10.1080/23737484.2020.1800535. Acesso em: 28 ago. 2024.
APA
Saraiva, E. F., Milan, L. A., & Pereira, C. A. de B. (2021). Bayesian criterion for identification of differentially expressed genes. Communications in Statistics: Case Studies, Data Analysis and Applications, 7( 1), 1-14. doi:10.1080/23737484.2020.1800535
NLM
Saraiva EF, Milan LA, Pereira CA de B. Bayesian criterion for identification of differentially expressed genes [Internet]. Communications in Statistics: Case Studies, Data Analysis and Applications. 2021 ; 7( 1): 1-14.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1080/23737484.2020.1800535
Vancouver
Saraiva EF, Milan LA, Pereira CA de B. Bayesian criterion for identification of differentially expressed genes [Internet]. Communications in Statistics: Case Studies, Data Analysis and Applications. 2021 ; 7( 1): 1-14.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1080/23737484.2020.1800535
Artigo de periodico
A Bayesian sparse finite mixture model for clustering data from a heterogeneous population (2020)
Saraiva, Erlandson Ferreira ; Suzuki, Adriano Kamimura ; Milan, Luis Aparecido
Source: Brazilian Journal of Probability and Statistics. Unidade: ICMC
Subjects: DISTRIBUIÇÕES (PROBABILIDADE), INFERÊNCIA BAYESIANA, AMOSTRAGEM, MÉTODO DE MONTE CARLO
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ABNT
SARAIVA, Erlandson Ferreira e SUZUKI, Adriano Kamimura e MILAN, Luis Aparecido. A Bayesian sparse finite mixture model for clustering data from a heterogeneous population. Brazilian Journal of Probability and Statistics, v. 34, n. 2, p. 323-344, 2020Tradução . . Disponível em: https://doi.org/10.1214/18-BJPS425. Acesso em: 28 ago. 2024.
APA
Saraiva, E. F., Suzuki, A. K., & Milan, L. A. (2020). A Bayesian sparse finite mixture model for clustering data from a heterogeneous population. Brazilian Journal of Probability and Statistics, 34( 2), 323-344. doi:10.1214/18-BJPS425
NLM
Saraiva EF, Suzuki AK, Milan LA. A Bayesian sparse finite mixture model for clustering data from a heterogeneous population [Internet]. Brazilian Journal of Probability and Statistics. 2020 ; 34( 2): 323-344.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1214/18-BJPS425
Vancouver
Saraiva EF, Suzuki AK, Milan LA. A Bayesian sparse finite mixture model for clustering data from a heterogeneous population [Internet]. Brazilian Journal of Probability and Statistics. 2020 ; 34( 2): 323-344.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1214/18-BJPS425
Artigo de periodico
Bayesian diagnostic analysis for quantitative trait loci mapping (2020)
Zuanetti, Daiane Aparecida ; Soler, Júlia Maria Pavan ; Krieger, José Eduardo ; Milan, Luis Aparecido
Source: Statistical Methods in Medical Research. Unidades: IME, FM
Assunto: INFERÊNCIA BAYESIANA
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ABNT
ZUANETTI, Daiane Aparecida et al. Bayesian diagnostic analysis for quantitative trait loci mapping. Statistical Methods in Medical Research, v. 29, n. 8, p. 2238-2249, 2020Tradução . . Disponível em: https://doi.org/10.1177/0962280219888950. Acesso em: 28 ago. 2024.
APA
Zuanetti, D. A., Soler, J. M. P., Krieger, J. E., & Milan, L. A. (2020). Bayesian diagnostic analysis for quantitative trait loci mapping. Statistical Methods in Medical Research, 29( 8), 2238-2249. doi:10.1177/0962280219888950
NLM
Zuanetti DA, Soler JMP, Krieger JE, Milan LA. Bayesian diagnostic analysis for quantitative trait loci mapping [Internet]. Statistical Methods in Medical Research. 2020 ; 29( 8): 2238-2249.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1177/0962280219888950
Vancouver
Zuanetti DA, Soler JMP, Krieger JE, Milan LA. Bayesian diagnostic analysis for quantitative trait loci mapping [Internet]. Statistical Methods in Medical Research. 2020 ; 29( 8): 2238-2249.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1177/0962280219888950
Artigo de periodico
An integrated approach for making inference on the number of clusters in a mixture model (2019)
Saraiva, Erlandson Ferreira ; Suzuki, Adriano Kamimura ; Milan, Luis Aparecido ; Pereira, Carlos Alberto de Bragança
Source: Entropy. Unidades: ICMC, IME, INTER: ICMC -UFSCAR
Subjects: PROBABILIDADE, PROCESSOS ESTOCÁSTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SARAIVA, Erlandson Ferreira et al. An integrated approach for making inference on the number of clusters in a mixture model. Entropy, v. 21, n. 11, p. 1-18, 2019Tradução . . Disponível em: https://doi.org/10.3390/e21111063. Acesso em: 28 ago. 2024.
APA
Saraiva, E. F., Suzuki, A. K., Milan, L. A., & Pereira, C. A. de B. (2019). An integrated approach for making inference on the number of clusters in a mixture model. Entropy, 21( 11), 1-18. doi:10.3390/e21111063
NLM
Saraiva EF, Suzuki AK, Milan LA, Pereira CA de B. An integrated approach for making inference on the number of clusters in a mixture model [Internet]. Entropy. 2019 ; 21( 11): 1-18.[citado 2024 ago. 28 ] Available from: https://doi.org/10.3390/e21111063
Vancouver
Saraiva EF, Suzuki AK, Milan LA, Pereira CA de B. An integrated approach for making inference on the number of clusters in a mixture model [Internet]. Entropy. 2019 ; 21( 11): 1-18.[citado 2024 ago. 28 ] Available from: https://doi.org/10.3390/e21111063
Artigo de periodico
Classification binary models for biomedical data: simple probabilistic networks and logistic regression (2018)
Ara, Anderson; Louzada, Francisco ; Milan, Luis Aparecido
Source: Revista Brasileira de Biometria. Unidade: ICMC
Subjects: INFERÊNCIA BAYESIANA, PROBABILIDADE, REGRESSÃO LOGÍSTICA, APRENDIZADO COMPUTACIONAL
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ABNT
ARA, Anderson e LOUZADA, Francisco e MILAN, Luis Aparecido. Classification binary models for biomedical data: simple probabilistic networks and logistic regression. Revista Brasileira de Biometria, v. 36, n. 1, p. 48-55, 2018Tradução . . Disponível em: https://doi.org/10.28951/rbb.v36i1.114. Acesso em: 28 ago. 2024.
APA
Ara, A., Louzada, F., & Milan, L. A. (2018). Classification binary models for biomedical data: simple probabilistic networks and logistic regression. Revista Brasileira de Biometria, 36( 1), 48-55. doi:10.28951/rbb.v36i1.114
NLM
Ara A, Louzada F, Milan LA. Classification binary models for biomedical data: simple probabilistic networks and logistic regression [Internet]. Revista Brasileira de Biometria. 2018 ; 36( 1): 48-55.[citado 2024 ago. 28 ] Available from: https://doi.org/10.28951/rbb.v36i1.114
Vancouver
Ara A, Louzada F, Milan LA. Classification binary models for biomedical data: simple probabilistic networks and logistic regression [Internet]. Revista Brasileira de Biometria. 2018 ; 36( 1): 48-55.[citado 2024 ago. 28 ] Available from: https://doi.org/10.28951/rbb.v36i1.114
Artigo de periodico
Bayesian computational methods for sampling from the posterior distribution of a bivariate survival model, based on AMH copula in the presence of right-censored data (2018)
Saraiva, Erlandson Ferreira; Suzuki, Adriano Kamimura ; Milan, Luis Aparecido
Source: Entropy. Unidade: ICMC
Subjects: INFERÊNCIA BAYESIANA, MÉTODOS MCMC
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SARAIVA, Erlandson Ferreira e SUZUKI, Adriano Kamimura e MILAN, Luis Aparecido. Bayesian computational methods for sampling from the posterior distribution of a bivariate survival model, based on AMH copula in the presence of right-censored data. Entropy, v. 20, n. 9, p. 1-21, 2018Tradução . . Disponível em: https://doi.org/10.3390/e20090642. Acesso em: 28 ago. 2024.
APA
Saraiva, E. F., Suzuki, A. K., & Milan, L. A. (2018). Bayesian computational methods for sampling from the posterior distribution of a bivariate survival model, based on AMH copula in the presence of right-censored data. Entropy, 20( 9), 1-21. doi:10.3390/e20090642
NLM
Saraiva EF, Suzuki AK, Milan LA. Bayesian computational methods for sampling from the posterior distribution of a bivariate survival model, based on AMH copula in the presence of right-censored data [Internet]. Entropy. 2018 ; 20( 9): 1-21.[citado 2024 ago. 28 ] Available from: https://doi.org/10.3390/e20090642
Vancouver
Saraiva EF, Suzuki AK, Milan LA. Bayesian computational methods for sampling from the posterior distribution of a bivariate survival model, based on AMH copula in the presence of right-censored data [Internet]. Entropy. 2018 ; 20( 9): 1-21.[citado 2024 ago. 28 ] Available from: https://doi.org/10.3390/e20090642
Artigo de periodico
Development and statistical assessment of paper-based immunoassay for detection of tumor markers (2017)
Mazzu Nascimento, Thiago; Morbioli, Giorgio Gianini; Milan, Luis Aparecido; Donofrio, Fabiana Cristina; Mestriner, Carlos Alberto; Carrilho, Emanuel
Source: Analytica Chimica Acta. Unidade: IQSC
Assunto: NEOPLASIAS
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ABNT
MAZZU NASCIMENTO, Thiago et al. Development and statistical assessment of paper-based immunoassay for detection of tumor markers. Analytica Chimica Acta, v. 950, p. 156-161, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.aca.2016.11.011. Acesso em: 28 ago. 2024.
APA
Mazzu Nascimento, T., Morbioli, G. G., Milan, L. A., Donofrio, F. C., Mestriner, C. A., & Carrilho, E. (2017). Development and statistical assessment of paper-based immunoassay for detection of tumor markers. Analytica Chimica Acta, 950, 156-161. doi:10.1016/j.aca.2016.11.011
NLM
Mazzu Nascimento T, Morbioli GG, Milan LA, Donofrio FC, Mestriner CA, Carrilho E. Development and statistical assessment of paper-based immunoassay for detection of tumor markers [Internet]. Analytica Chimica Acta. 2017 ; 950 156-161.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1016/j.aca.2016.11.011
Vancouver
Mazzu Nascimento T, Morbioli GG, Milan LA, Donofrio FC, Mestriner CA, Carrilho E. Development and statistical assessment of paper-based immunoassay for detection of tumor markers [Internet]. Analytica Chimica Acta. 2017 ; 950 156-161.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1016/j.aca.2016.11.011
Artigo de periodico
Improving sample distribution homogeneity in three-dimensional microfluidic paper-based analytical devices by rational device design (2017)
Morbioli, Giorgio Gianini; Mazzu Nascimento, Thiago; Milan, Luis Aparecido; Stockton, Amanda M; Carrilho, Emanuel
Source: Analytical Chemistry. Unidade: IQSC
Assunto: QUÍMICA ANALÍTICA
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ABNT
MORBIOLI, Giorgio Gianini et al. Improving sample distribution homogeneity in three-dimensional microfluidic paper-based analytical devices by rational device design. Analytical Chemistry, v. 89, p. 4786-4792, 2017Tradução . . Disponível em: https://doi.org/10.1021/acs.analchem.6b04953. Acesso em: 28 ago. 2024.
APA
Morbioli, G. G., Mazzu Nascimento, T., Milan, L. A., Stockton, A. M., & Carrilho, E. (2017). Improving sample distribution homogeneity in three-dimensional microfluidic paper-based analytical devices by rational device design. Analytical Chemistry, 89, 4786-4792. doi:10.1021/acs.analchem.6b04953
NLM
Morbioli GG, Mazzu Nascimento T, Milan LA, Stockton AM, Carrilho E. Improving sample distribution homogeneity in three-dimensional microfluidic paper-based analytical devices by rational device design [Internet]. Analytical Chemistry. 2017 ; 89 4786-4792.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1021/acs.analchem.6b04953
Vancouver
Morbioli GG, Mazzu Nascimento T, Milan LA, Stockton AM, Carrilho E. Improving sample distribution homogeneity in three-dimensional microfluidic paper-based analytical devices by rational device design [Internet]. Analytical Chemistry. 2017 ; 89 4786-4792.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1021/acs.analchem.6b04953
Artigo de periodico
Bayesian estimation for a mixture of simplex distributions with an unknown number of components Brazil: HDI analysis in Brazil (2017)
Paz, Rosineide Fernando da; Bazán Guzmán, Jorge Luis ; Milan, Luis Aparecido
Source: Journal of Applied Statistics. Unidade: ICMC
Subjects: PROCESSOS ESTOCÁSTICOS, INFERÊNCIA BAYESIANA, INFERÊNCIA ESTATÍSTICA, INFERÊNCIA PARAMÉTRICA, PROBABILIDADE
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ABNT
PAZ, Rosineide Fernando da e BAZÁN GUZMÁN, Jorge Luis e MILAN, Luis Aparecido. Bayesian estimation for a mixture of simplex distributions with an unknown number of components Brazil: HDI analysis in Brazil. Journal of Applied Statistics, v. 44, n. 9, p. 1630-1643, 2017Tradução . . Disponível em: https://doi.org/10.1080/02664763.2016.1221903. Acesso em: 28 ago. 2024.
APA
Paz, R. F. da, Bazán Guzmán, J. L., & Milan, L. A. (2017). Bayesian estimation for a mixture of simplex distributions with an unknown number of components Brazil: HDI analysis in Brazil. Journal of Applied Statistics, 44( 9), 1630-1643. doi:10.1080/02664763.2016.1221903
NLM
Paz RF da, Bazán Guzmán JL, Milan LA. Bayesian estimation for a mixture of simplex distributions with an unknown number of components Brazil: HDI analysis in Brazil [Internet]. Journal of Applied Statistics. 2017 ; 44( 9): 1630-1643.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1080/02664763.2016.1221903
Vancouver
Paz RF da, Bazán Guzmán JL, Milan LA. Bayesian estimation for a mixture of simplex distributions with an unknown number of components Brazil: HDI analysis in Brazil [Internet]. Journal of Applied Statistics. 2017 ; 44( 9): 1630-1643.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1080/02664763.2016.1221903
Artigo de periodico
Improved assessment of accuracy and performance indicators in paper-based ELISA (2017)
Mazzu Nascimento, Thiago; Morbioli, Giorgio Gianni; Milan, Luis Aparecido; Silva, Diego Furtado ; Donofrio, Fabiana Cristina; Mestriner, Carlos Alberto; Carrilho, Emanuel
Source: Analytical Methods. Unidade: IQSC
Subjects: PAPEL, QUÍMICA ANALÍTICA, ENSAIO CLÍNICO
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ABNT
MAZZU NASCIMENTO, Thiago et al. Improved assessment of accuracy and performance indicators in paper-based ELISA. Analytical Methods, v. 9, p. 2644-2653, 2017Tradução . . Disponível em: https://doi.org/10.1039/c7ay00505a. Acesso em: 28 ago. 2024.
APA
Mazzu Nascimento, T., Morbioli, G. G., Milan, L. A., Silva, D. F., Donofrio, F. C., Mestriner, C. A., & Carrilho, E. (2017). Improved assessment of accuracy and performance indicators in paper-based ELISA. Analytical Methods, 9, 2644-2653. doi:10.1039/c7ay00505a
NLM
Mazzu Nascimento T, Morbioli GG, Milan LA, Silva DF, Donofrio FC, Mestriner CA, Carrilho E. Improved assessment of accuracy and performance indicators in paper-based ELISA [Internet]. Analytical Methods. 2017 ; 9 2644-2653.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1039/c7ay00505a
Vancouver
Mazzu Nascimento T, Morbioli GG, Milan LA, Silva DF, Donofrio FC, Mestriner CA, Carrilho E. Improved assessment of accuracy and performance indicators in paper-based ELISA [Internet]. Analytical Methods. 2017 ; 9 2644-2653.[citado 2024 ago. 28 ] Available from: https://doi.org/10.1039/c7ay00505a

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