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bayesvl: Visually learning the graphical structure of Bayesian networks and performing MCMC with ‘Stan’
Vienna, Austria: The Comprehensive R Archive Network (CRAN) (2019)
Abstract
La, V. P., & Vuong, Q. H. (2019). bayesvl: Visually learning the graphical structure of Bayesian networks and performing MCMC with ‘Stan’. The Comprehensive R Archive Network (CRAN).Other Versions
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Citations of this work
BMF CP69: Interactions between varying economic options and varying wherewithals in mitigating climate change and biodiversity loss consequences.A. I. S. D. L. Team - 2024 - Sm3D Portal.
Học liệu BMF analytics hiện diện tại Harvard University HOLLIS.Tổ Kỹ Thuật Aisdl - 2024 - Bmf Method.
References found in this work
Open data, open review and open dialogue in making social sciences plausible.Quan-Hoang Vuong - 2017 - Nature: Scientific Data Updates 2017.
Academic research: the difficulty of being simple and beautiful.Quan-Hoang Vuong & Nancy K. Napier - 2017 - European Science Editing 43 (2):32-33.
Black-Scholes PDE: A Finance Application.Quan-Hoang Vuong - 2001 - In International Conference on Differential Equations, Approximations and Applications, DEAA - 2001. pp. 53-53.
bayesvl: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with 'Stan'.Quan-Hoang Vuong & Viet-Phuong La - 2019 - Open Science Framework 2019:01-47.
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