Bayesian Analysis of Location-Scale Mixture Models using a Weakly Informative Prior

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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


2.1 by Kaniav Kamary, 5 years ago

Browse source code at

Authors: Kaniav Kamary , Kate Lee

Documentation:   PDF Manual  

GPL (>= 2.0) license

Depends on coda, gtools, graphics, grDevices, stats

See at CRAN