Bayesian model and posterior distribution dataset for estimating the distribution of ¹³⁷Cs concentrations in various wild mushroom species in Japanese municipalities

<h4>Komatsu_2023JJFS_stan_model.stan</h4> <p>    - Model file for Bayesian analysis with rstan.</p> <p>    - 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).</p> <p>    - Consists of eqs. (1)-(5) in RELATED MATERIALS 1.</p> <h4>post_stan.RData</h4> <p>    - RData file to store the results of the posterior distribution obtained by the hierarchical Bayesian model (post: variables in list format)</p> <p>        - post$species: species names corresponding to columns in rsp and rsigma</p> <p>        - post$rsp: random effect of species</p> <p>        - post$rsigma: standard deviation of individuals by species</p> <p>        - post$mu_sp: hyper parameter of mean in rsp</p> <p>        - post$sigma_sp: hyper parameter of standard deviation in rsp</p> <p>        - post$mu_sigma: hyper parameter of mu in rsigma</p> <p>        - post$sigma_sigma: hyper parameter of standard deviation in rsigma</p> <p>        - post$sigma_mun: hyper parameter of standard deviation in rmun</p> <p>    - Posterior results of random effects of municipality (rmun) is excluded.</p>