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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 |
| Reference manual: | Ultimixt.pdf |
| Package source: | Ultimixt_2.1.tar.gz |
| Windows binaries: | r-devel: Ultimixt_2.1.zip, r-release: Ultimixt_2.1.zip, r-oldrel: Ultimixt_2.1.zip |
| macOS binaries: | r-release (arm64): Ultimixt_2.1.tgz, r-oldrel (arm64): Ultimixt_2.1.tgz, r-release (x86_64): Ultimixt_2.1.tgz, r-oldrel (x86_64): Ultimixt_2.1.tgz |
| Old sources: | Ultimixt archive |
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