Bayesian Mixture Models with JAGS
Plot identifiability diagnostics for JAGSrun object
Creates bugs model.
Plot aposteriori probabilities of data points
Create a 'BMMpriors' object
Differences in heights between plants
Fish length data
Create initial values
Call jags
Control parameters for the sampling.
MCMC sampling of Bayesian models
Plot a posteriori probabilities of data points
Plot JAGSrun object
Create list of prior specifications
Randomly permute segments for MCMC draws
Sort MCMC chains according to certain variables
Fits finite mixture models of univariate Gaussian distributions using JAGS within a Bayesian framework.