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pro vyhledávání: '"Bayesian hierarchical models"'
The power prior is a popular class of informative priors for incorporating information from historical data. It involves raising the likelihood for the historical data to a power, which acts as a discounting parameter. When the discounting parameter
Externí odkaz:
http://arxiv.org/abs/2404.02453
Autor:
Li, Dayi, Zhang, Ziang
Approximate Bayesian inference based on Laplace approximation and quadrature methods have become increasingly popular for their efficiency at fitting latent Gaussian models (LGM), which encompass popular models such as Bayesian generalized linear mod
Externí odkaz:
http://arxiv.org/abs/2403.12250
Publikováno v:
Heliyon, Volume 10, Issue 6, 2024, e27968
One-shirt-size policy cannot handle poverty issues well since each area has its unique challenges, while having a custom-made policy for each area separately is unrealistic due to limitation of resources as well as having issues of ignoring dependenc
Externí odkaz:
http://arxiv.org/abs/2308.16578
Autor:
Zhong, Ruiman1 (AUTHOR) ruiman.zhong@kaust.edu.sa, Moraga, Paula1 (AUTHOR)
Publikováno v:
Journal of Agricultural, Biological & Environmental Statistics (JABES). Mar2024, Vol. 29 Issue 1, p110-129. 20p.
Autor:
Ascolani, Filippo, Zanella, Giacomo
Gibbs samplers are popular algorithms to approximate posterior distributions arising from Bayesian hierarchical models. Despite their popularity and good empirical performances, however, there are still relatively few quantitative results on their co
Externí odkaz:
http://arxiv.org/abs/2304.06993
Autor:
Shergina, Elena1 (AUTHOR) e696s865@kumc.edu, Richter, Kimber P.2 (AUTHOR), Makosky Daley, Christine3 (AUTHOR), Faseru, Babalola2 (AUTHOR), Choi, Won S.3 (AUTHOR), Gajewski, Byron J.1 (AUTHOR)
Publikováno v:
Journal of Biopharmaceutical Statistics. 2024, Vol. 34 Issue 4, p513-525. 13p.
Akademický článek
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Akademický článek
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Autor:
Zilber, Daniel1 (AUTHOR), Messier, Kyle1 (AUTHOR) kyle.messier@nih.gov
Publikováno v:
PLoS ONE. 3/28/2024, Vol. 19 Issue 3, p1-23. 23p.