Bayesian model and posterior distribution dataset for estimating the distribution of 137Cs concentrations in various wild mushroom species in Japanese municipalities
- Model file for Bayesian analysis with rstan.
- Hierarchical Bayesian model with the ordinary logarithm of 137Cs concentration in wild mushrooms as the objective variable and the random effects of the mean concentration for species (r_sp), the error in concentration per species (r_sigma) and the concentration effect per municipality (r_mun).
- Consists of eqs. (1)-(5) in RELATED MATERIALS 1.
- RData file to store the results of the posterior distribution obtained by the hierarchical Bayesian model (post: variables in list format)
- post$species: species names corresponding to columns in rsp and rsigma
- post$rsp: random effect of species
- post$rsigma: standard deviation of individuals by species
- post$mu_sp: hyper parameter of mean in rsp
- post$sigma_sp: hyper parameter of standard deviation in rsp
- post$mu_sigma: hyper parameter of mu in rsigma
- post$sigma_sigma: hyper parameter of standard deviation in rsigma
- post$sigma_mun: hyper parameter of standard deviation in rmun
- Posterior results of random effects of municipality (rmun) is excluded.
Production of low-cesium mushrooms based on the genes analysis
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