Source: Fisheries Research. Unidade: IME
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, MODELOS EM SÉRIES TEMPORAIS, INFERÊNCIA BAYESIANA, MÉTODO DE MONTE CARLO, CAMARÃO
ABNT
MONTENEGRO, Carlos e BRANCO, Marcia D'Elia. Bayesian state-space approach to biomass dynamic models with skewed and heavy-tailed error distributions. Fisheries Research, v. 181, p. 48-62, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.fishres.2016.03.021. Acesso em: 16 nov. 2024.APA
Montenegro, C., & Branco, M. D. 'E. (2016). Bayesian state-space approach to biomass dynamic models with skewed and heavy-tailed error distributions. Fisheries Research, 181, 48-62. doi:10.1016/j.fishres.2016.03.021NLM
Montenegro C, Branco MD'E. Bayesian state-space approach to biomass dynamic models with skewed and heavy-tailed error distributions [Internet]. Fisheries Research. 2016 ; 181 48-62.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.fishres.2016.03.021Vancouver
Montenegro C, Branco MD'E. Bayesian state-space approach to biomass dynamic models with skewed and heavy-tailed error distributions [Internet]. Fisheries Research. 2016 ; 181 48-62.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.fishres.2016.03.021