Ultimixt: 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.
| Version: |
2.1 |
| Depends: |
coda, gtools, graphics, grDevices, stats |
| Published: |
2017-03-09 |
| Author: |
Kaniav Kamary, Kate Lee |
| Maintainer: |
Kaniav Kamary <kamary at ceremade.dauphine.fr> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)] |
| NeedsCompilation: |
no |
| CRAN checks: |
Ultimixt results |
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