ReP USP - Resultado da busca

Filtros : "Paquistão" "2022" "FMRP" Removidos: "Japão" "FMRP-RMF" "Holanda" "Arquivos de Gastroenterologia" Limpar

Filtros

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
Fonte: Pakistan Journal of Statistics and Operation Research. Unidade: FMRP
Assuntos: 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: 14 nov. 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 nov. 14 ] 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 nov. 14 ] Available from: https://doi.org/10.18187/pjsor.v18i2.3976
Artigo de periodico
Bayesian bivariate spatial shared component model: mapping breast and cervical cancer mortality in Southern Brazil (2022)
Martinez, Edson Zangiacomi ; Silva, Diego Gafuri; Resende, Larissa Intrebartoli; Lizzi, Elisangela Aparecida da Silva; Achcar, Jorge Alberto
Fonte: Pakistan Journal of Statistics and Operation Research. Unidade: FMRP
Assuntos: ESTUDOS ECOLÓGICOS, EPIDEMIOLOGIA, INFERÊNCIA ESTATÍSTICA, PROCESSOS ESTOCÁSTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTINEZ, Edson Zangiacomi et al. Bayesian bivariate spatial shared component model: mapping breast and cervical cancer mortality in Southern Brazil. Pakistan Journal of Statistics and Operation Research, v. 18, n. 4, p. 775-788, 2022Tradução . . Disponível em: https://doi.org/10.18187/pjsor.v18i4.4095. Acesso em: 14 nov. 2024.
APA
Martinez, E. Z., Silva, D. G., Resende, L. I., Lizzi, E. A. da S., & Achcar, J. A. (2022). Bayesian bivariate spatial shared component model: mapping breast and cervical cancer mortality in Southern Brazil. Pakistan Journal of Statistics and Operation Research, 18( 4), 775-788. doi:10.18187/pjsor.v18i4.4095
NLM
Martinez EZ, Silva DG, Resende LI, Lizzi EA da S, Achcar JA. Bayesian bivariate spatial shared component model: mapping breast and cervical cancer mortality in Southern Brazil [Internet]. Pakistan Journal of Statistics and Operation Research. 2022 ; 18( 4): 775-788.[citado 2024 nov. 14 ] Available from: https://doi.org/10.18187/pjsor.v18i4.4095
Vancouver
Martinez EZ, Silva DG, Resende LI, Lizzi EA da S, Achcar JA. Bayesian bivariate spatial shared component model: mapping breast and cervical cancer mortality in Southern Brazil [Internet]. Pakistan Journal of Statistics and Operation Research. 2022 ; 18( 4): 775-788.[citado 2024 nov. 14 ] Available from: https://doi.org/10.18187/pjsor.v18i4.4095

Biblioteca Digital de Produção Intelectual da Universidade de São Paulo 2012 - 2024