ReP USP - Resultado da busca

Artigo de periodico
Semiparametric transformation model: a hierarchical Bayesian approach (2023)
Achcar, Jorge Alberto; Barili, Emerson; Martinez, Edson Zangiacomi
Source: Model Assisted Statistics and Applications. Unidade: FMRP
Subjects: DADOS CENSURADOS, INFERÊNCIA BAYESIANA, MÉTODOS MCMC
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ACHCAR, Jorge Alberto e BARILI, Emerson e MARTINEZ, Edson Zangiacomi. Semiparametric transformation model: a hierarchical Bayesian approach. Model Assisted Statistics and Applications, v. 18, p. 245-256, 2023Tradução . . Disponível em: https://doi.org/10.3233/MAS-221408. Acesso em: 01 out. 2024.
APA
Achcar, J. A., Barili, E., & Martinez, E. Z. (2023). Semiparametric transformation model: a hierarchical Bayesian approach. Model Assisted Statistics and Applications, 18, 245-256. doi:10.3233/MAS-221408
NLM
Achcar JA, Barili E, Martinez EZ. Semiparametric transformation model: a hierarchical Bayesian approach [Internet]. Model Assisted Statistics and Applications. 2023 ; 18 245-256.[citado 2024 out. 01 ] Available from: https://doi.org/10.3233/MAS-221408
Vancouver
Achcar JA, Barili E, Martinez EZ. Semiparametric transformation model: a hierarchical Bayesian approach [Internet]. Model Assisted Statistics and Applications. 2023 ; 18 245-256.[citado 2024 out. 01 ] Available from: https://doi.org/10.3233/MAS-221408
Artigo de periodico
Use of segmented linear regression under a bayesian approach to detect climate change in different regions of the world (2023)
Barili, Emerson; Achcar, Jorge Alberto
Source: Biomedical Science and Clinical Research. Unidade: FMRP
Subjects: MUDANÇA CLIMÁTICA, REGRESSÃO LINEAR, PRECIPITAÇÃO ATMOSFÉRICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARILI, Emerson e ACHCAR, Jorge Alberto. Use of segmented linear regression under a bayesian approach to detect climate change in different regions of the world. Biomedical Science and Clinical Research, v. 2, n. 1, p. 149-158, 2023Tradução . . Disponível em: https://doi.org/10.33140/BSCR. Acesso em: 01 out. 2024.
APA
Barili, E., & Achcar, J. A. (2023). Use of segmented linear regression under a bayesian approach to detect climate change in different regions of the world. Biomedical Science and Clinical Research, 2( 1), 149-158. doi:10.33140/BSCR
NLM
Barili E, Achcar JA. Use of segmented linear regression under a bayesian approach to detect climate change in different regions of the world [Internet]. Biomedical Science and Clinical Research. 2023 ; 2( 1): 149-158.[citado 2024 out. 01 ] Available from: https://doi.org/10.33140/BSCR
Vancouver
Barili E, Achcar JA. Use of segmented linear regression under a bayesian approach to detect climate change in different regions of the world [Internet]. Biomedical Science and Clinical Research. 2023 ; 2( 1): 149-158.[citado 2024 out. 01 ] Available from: https://doi.org/10.33140/BSCR
Artigo de periodico
Climate Change Data: Use of an Autoregressive (AR) Model in Presence of Change Points under a Bayesian Approach (2023)
Achcar, Jorge Alberto; Barili, Emerson
Source: International Journal of Environment and Climate Change. Unidade: FMRP
Subjects: CLIMA, MÉTODOS MCMC, INFERÊNCIA BAYESIANA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ACHCAR, Jorge Alberto e BARILI, Emerson. Climate Change Data: Use of an Autoregressive (AR) Model in Presence of Change Points under a Bayesian Approach. International Journal of Environment and Climate Change, v. 13, n. 6, p. 23-47, 2023Tradução . . Disponível em: https://doi.org/10.9734/ijecc/2023/v13i61795. Acesso em: 01 out. 2024.
APA
Achcar, J. A., & Barili, E. (2023). Climate Change Data: Use of an Autoregressive (AR) Model in Presence of Change Points under a Bayesian Approach. International Journal of Environment and Climate Change, 13( 6), 23-47. doi:10.9734/ijecc/2023/v13i61795
NLM
Achcar JA, Barili E. Climate Change Data: Use of an Autoregressive (AR) Model in Presence of Change Points under a Bayesian Approach [Internet]. International Journal of Environment and Climate Change. 2023 ; 13( 6): 23-47.[citado 2024 out. 01 ] Available from: https://doi.org/10.9734/ijecc/2023/v13i61795
Vancouver
Achcar JA, Barili E. Climate Change Data: Use of an Autoregressive (AR) Model in Presence of Change Points under a Bayesian Approach [Internet]. International Journal of Environment and Climate Change. 2023 ; 13( 6): 23-47.[citado 2024 out. 01 ] Available from: https://doi.org/10.9734/ijecc/2023/v13i61795
Artigo de periodico
Annual mean temperature and rain precipitation in North America using NHPP to detect climate changes (2023)
Achcar, Jorge Alberto; Rodrigues, Eliane R.; Oliveira, Ricardo Puziol de; Barili, Emerson
Source: International Journal of Environment and Climate Change. Unidade: FMRP
Subjects: MUDANÇA CLIMÁTICA, INFERÊNCIA BAYESIANA, MÉTODOS MCMC
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ACHCAR, Jorge Alberto et al. Annual mean temperature and rain precipitation in North America using NHPP to detect climate changes. International Journal of Environment and Climate Change, v. 13, n. 8, p. 141-161, 2023Tradução . . Disponível em: https://doi.org/10.9734/IJECC/2023/v13i81940. Acesso em: 01 out. 2024.
APA
Achcar, J. A., Rodrigues, E. R., Oliveira, R. P. de, & Barili, E. (2023). Annual mean temperature and rain precipitation in North America using NHPP to detect climate changes. International Journal of Environment and Climate Change, 13( 8), 141-161. doi:10.9734/IJECC/2023/v13i81940
NLM
Achcar JA, Rodrigues ER, Oliveira RP de, Barili E. Annual mean temperature and rain precipitation in North America using NHPP to detect climate changes [Internet]. International Journal of Environment and Climate Change. 2023 ; 13( 8): 141-161.[citado 2024 out. 01 ] Available from: https://doi.org/10.9734/IJECC/2023/v13i81940
Vancouver
Achcar JA, Rodrigues ER, Oliveira RP de, Barili E. Annual mean temperature and rain precipitation in North America using NHPP to detect climate changes [Internet]. International Journal of Environment and Climate Change. 2023 ; 13( 8): 141-161.[citado 2024 out. 01 ] Available from: https://doi.org/10.9734/IJECC/2023/v13i81940
Artigo de periodico
Spatial-temporal factors affecting monthly rainfall in some Central Asian countries assuming a Weibull regression model (2022)
Barili, Emerson; Achcar, Jorge Alberto ; Oliveira, Ricardo Puziol de
Source: Pakistan Journal of Statistics and Operation Research. Unidade: FMRP
Subjects: SÉRIES ESPAÇO-TEMPORAIS, VEROSSIMILHANÇA, MUDANÇA CLIMÁTICA, PRECIPITAÇÃO ATMOSFÉRICA, ANÁLISE DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARILI, Emerson e ACHCAR, Jorge Alberto e OLIVEIRA, Ricardo Puziol de. Spatial-temporal factors affecting monthly rainfall in some Central Asian countries assuming a Weibull regression model. Pakistan Journal of Statistics and Operation Research, v. 18, n. 2, p. 465-482, 2022Tradução . . Disponível em: https://doi.org/10.18187/pjsor.v18i2.3976. Acesso em: 01 out. 2024.
APA
Barili, E., Achcar, J. A., & Oliveira, R. P. de. (2022). Spatial-temporal factors affecting monthly rainfall in some Central Asian countries assuming a Weibull regression model. Pakistan Journal of Statistics and Operation Research, 18( 2), 465-482. doi:10.18187/pjsor.v18i2.3976
NLM
Barili E, Achcar JA, Oliveira RP de. Spatial-temporal factors affecting monthly rainfall in some Central Asian countries assuming a Weibull regression model [Internet]. Pakistan Journal of Statistics and Operation Research. 2022 ; 18( 2): 465-482.[citado 2024 out. 01 ] Available from: https://doi.org/10.18187/pjsor.v18i2.3976
Vancouver
Barili E, Achcar JA, Oliveira RP de. Spatial-temporal factors affecting monthly rainfall in some Central Asian countries assuming a Weibull regression model [Internet]. Pakistan Journal of Statistics and Operation Research. 2022 ; 18( 2): 465-482.[citado 2024 out. 01 ] Available from: https://doi.org/10.18187/pjsor.v18i2.3976
Parte de monografia/livro
Algumas considerações sobre o uso de métodos bayesianos na área médica e de saúde pública (2022)
Achcar, Jorge Alberto; Barili, Emerson
Source: Pesquisas em clínica médica. Unidade: FMRP
Subjects: INFERÊNCIA BAYESIANA, SAÚDE PÚBLICA, EPIDEMIOLOGIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ACHCAR, Jorge Alberto e BARILI, Emerson. Algumas considerações sobre o uso de métodos bayesianos na área médica e de saúde pública. Pesquisas em clínica médica. Tradução . Campina Grande: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 2022. . Disponível em: https://doi.org/10.56001/22.9786500533422. Acesso em: 01 out. 2024.
APA
Achcar, J. A., & Barili, E. (2022). Algumas considerações sobre o uso de métodos bayesianos na área médica e de saúde pública. In Pesquisas em clínica médica. Campina Grande: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.56001/22.9786500533422
NLM
Achcar JA, Barili E. Algumas considerações sobre o uso de métodos bayesianos na área médica e de saúde pública [Internet]. In: Pesquisas em clínica médica. Campina Grande: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo; 2022. [citado 2024 out. 01 ] Available from: https://doi.org/10.56001/22.9786500533422
Vancouver
Achcar JA, Barili E. Algumas considerações sobre o uso de métodos bayesianos na área médica e de saúde pública [Internet]. In: Pesquisas em clínica médica. Campina Grande: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo; 2022. [citado 2024 out. 01 ] Available from: https://doi.org/10.56001/22.9786500533422
Parte de monografia/livro
Effect of the covid-19 pandemic in the total monthly death counts in the year 2020 for all Brazilian states (2022)
Oliveira, Ricardo Puziol de; Peres, Marcos Vinicius de Oliveira; Barili, Emerson; Rodrigues, Hugo Murilo; Souza, José Bruno Pereira; Santos, Franchesco Sanches dos; Lima, Vanessa de Oliveira; Leiria, Talisson Fernando; Achcar, Jorge Alberto ; Martinez, Edson Zangiacomi
Source: Open Science Research V. Unidade: FMRP
Subjects: INFERÊNCIA BAYESIANA, MORTE, COVID-19, DADOS DE CONTAGEM, ESTUDOS ECOLÓGICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Ricardo Puziol de et al. Effect of the covid-19 pandemic in the total monthly death counts in the year 2020 for all Brazilian states. Open Science Research V. Tradução . Guarujá: Científica Digital, 2022. . Disponível em: https://doi.org/10.37885/220709577. Acesso em: 01 out. 2024.
APA
Oliveira, R. P. de, Peres, M. V. de O., Barili, E., Rodrigues, H. M., Souza, J. B. P., Santos, F. S. dos, et al. (2022). Effect of the covid-19 pandemic in the total monthly death counts in the year 2020 for all Brazilian states. In Open Science Research V. Guarujá: Científica Digital. doi:10.37885/220709577
NLM
Oliveira RP de, Peres MV de O, Barili E, Rodrigues HM, Souza JBP, Santos FS dos, Lima V de O, Leiria TF, Achcar JA, Martinez EZ. Effect of the covid-19 pandemic in the total monthly death counts in the year 2020 for all Brazilian states [Internet]. In: Open Science Research V. Guarujá: Científica Digital; 2022. [citado 2024 out. 01 ] Available from: https://doi.org/10.37885/220709577
Vancouver
Oliveira RP de, Peres MV de O, Barili E, Rodrigues HM, Souza JBP, Santos FS dos, Lima V de O, Leiria TF, Achcar JA, Martinez EZ. Effect of the covid-19 pandemic in the total monthly death counts in the year 2020 for all Brazilian states [Internet]. In: Open Science Research V. Guarujá: Científica Digital; 2022. [citado 2024 out. 01 ] Available from: https://doi.org/10.37885/220709577
Artigo de periodico
The incidence of tuberculosis in Brazil from 2001 to 2018: use of polynomial regression combined with a stochastic volatility model (2021)
Achcar, Jorge Alberto ; Oliveira, Ricardo Puziol de; Barili, Emerson
Source: International Journal of Clinical Biostatistics and Biometrics. Unidade: FMRP
Subjects: MÉTODOS MCMC, REGRESSÃO LINEAR, MODELOS PARA PROCESSOS ESTOCÁSTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ACHCAR, Jorge Alberto e OLIVEIRA, Ricardo Puziol de e BARILI, Emerson. The incidence of tuberculosis in Brazil from 2001 to 2018: use of polynomial regression combined with a stochastic volatility model. International Journal of Clinical Biostatistics and Biometrics, v. 7, n. 1, 2021Tradução . . Disponível em: https://doi.org/10.23937/2469-5831/1510035. Acesso em: 01 out. 2024.
APA
Achcar, J. A., Oliveira, R. P. de, & Barili, E. (2021). The incidence of tuberculosis in Brazil from 2001 to 2018: use of polynomial regression combined with a stochastic volatility model. International Journal of Clinical Biostatistics and Biometrics, 7( 1). doi:10.23937/2469-5831/1510035
NLM
Achcar JA, Oliveira RP de, Barili E. The incidence of tuberculosis in Brazil from 2001 to 2018: use of polynomial regression combined with a stochastic volatility model [Internet]. International Journal of Clinical Biostatistics and Biometrics. 2021 ; 7( 1):[citado 2024 out. 01 ] Available from: https://doi.org/10.23937/2469-5831/1510035
Vancouver
Achcar JA, Oliveira RP de, Barili E. The incidence of tuberculosis in Brazil from 2001 to 2018: use of polynomial regression combined with a stochastic volatility model [Internet]. International Journal of Clinical Biostatistics and Biometrics. 2021 ; 7( 1):[citado 2024 out. 01 ] Available from: https://doi.org/10.23937/2469-5831/1510035
Artigo de periodico
Use of stochastic volatility models in epidemiological data: application to a dengue time series in São Paulo city, Brazil (2020)
Achcar, Jorge Alberto ; Oliveira, Ricardo Puziol de; Barili, Emerson
Source: Journal of Biostatistics and Epidemiology. Unidade: FMRP
Subjects: DENGUE, MÉTODOS MCMC, MODELOS EPIDEMIOLOGICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ACHCAR, Jorge Alberto e OLIVEIRA, Ricardo Puziol de e BARILI, Emerson. Use of stochastic volatility models in epidemiological data: application to a dengue time series in São Paulo city, Brazil. Journal of Biostatistics and Epidemiology, v. 6, n. 1, p. 19-29, 2020Tradução . . Disponível em: https://doi.org/10.18502/jbe.v6i1.4755. Acesso em: 01 out. 2024.
APA
Achcar, J. A., Oliveira, R. P. de, & Barili, E. (2020). Use of stochastic volatility models in epidemiological data: application to a dengue time series in São Paulo city, Brazil. Journal of Biostatistics and Epidemiology, 6( 1), 19-29. doi:10.18502/jbe.v6i1.4755
NLM
Achcar JA, Oliveira RP de, Barili E. Use of stochastic volatility models in epidemiological data: application to a dengue time series in São Paulo city, Brazil [Internet]. Journal of Biostatistics and Epidemiology. 2020 ; 6( 1): 19-29.[citado 2024 out. 01 ] Available from: https://doi.org/10.18502/jbe.v6i1.4755
Vancouver
Achcar JA, Oliveira RP de, Barili E. Use of stochastic volatility models in epidemiological data: application to a dengue time series in São Paulo city, Brazil [Internet]. Journal of Biostatistics and Epidemiology. 2020 ; 6( 1): 19-29.[citado 2024 out. 01 ] Available from: https://doi.org/10.18502/jbe.v6i1.4755

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