Bayesian Analysis of Location-Scale Mixture Models using a Weakly Informative Prior
Sample from a Poisson mixture posterior associated with a noninformati...
Sample from a Gaussian mixture posterior associated with a noninformat...
plot of the MCMC output produced by K.MixReparametrized
summary of the output produced by K.MixReparametrized
summary of the output produced by K.MixPois
summary of the output produced by K.MixReparametrized
set of R functions for estimating the parameters of mixture distributi...
A generic reference Bayesian analysis of unidimensional mixture distributions obtained by a location-scale parameterisation of the model is implemented. The including functions simulate and summarize posterior samples for location-scale mixture models using a weakly informative prior. There is no need to define priors for scale-location parameters except two hyperparameters in which are associated with a Dirichlet prior for weights and a simplex.