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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
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
Artigo de periodico
Climate change: use of non-homogeneous poisson processes for climate data in presence of a change-point (2022)
Achcar, Jorge Alberto ; Oliveira, Ricardo Puziol de
Source: Environmental Modeling & Assessment. Unidade: FMRP
Subjects: TEMPERATURA, PRECIPITAÇÃO, MÉTODOS MCMC, MUDANÇA CLIMÁTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ACHCAR, Jorge Alberto e OLIVEIRA, Ricardo Puziol de. Climate change: use of non-homogeneous poisson processes for climate data in presence of a change-point. Environmental Modeling & Assessment, v. 27, p. 385-398, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10666-021-09797-z. Acesso em: 01 out. 2024.
APA
Achcar, J. A., & Oliveira, R. P. de. (2022). Climate change: use of non-homogeneous poisson processes for climate data in presence of a change-point. Environmental Modeling & Assessment, 27, 385-398. doi:10.1007/s10666-021-09797-z
NLM
Achcar JA, Oliveira RP de. Climate change: use of non-homogeneous poisson processes for climate data in presence of a change-point [Internet]. Environmental Modeling & Assessment. 2022 ; 27 385-398.[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/s10666-021-09797-z
Vancouver
Achcar JA, Oliveira RP de. Climate change: use of non-homogeneous poisson processes for climate data in presence of a change-point [Internet]. Environmental Modeling & Assessment. 2022 ; 27 385-398.[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/s10666-021-09797-z

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