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.

Install the latest version of this package by entering the following in R:

`install.packages("Ultimixt")`

Author | Kaniav Kamary, Kate Lee |

Date of publication | 2017-03-09 00:33:27 |

Maintainer | Kaniav Kamary <kamary@ceremade.dauphine.fr> |

License | GPL (>= 2.0) |

Version | 2.1 |

**K.MixPois:** Sample from a Poisson mixture posterior associated with a...

**K.MixReparametrized:** Sample from a Gaussian mixture posterior associated with a...

**Plot.MixReparametrized:** plot of the MCMC output produced by K.MixReparametrized

**SM.MAP.MixReparametrized:** summary of the output produced by K.MixReparametrized

**SM.MixPois:** summary of the output produced by K.MixPois

**SM.MixReparametrized:** summary of the output produced by K.MixReparametrized

**Ultimixt-package:** set of R functions for estimating the parameters of mixture...

NAMESPACE

R

R/SM.MixReparametrized.R
R/K.MixPois.R
R/K.MixReparametrized.R
R/Plot.MixReparametrized.R
R/SM.MixPois.R
R/SM.MAP.MixReparametrized.R
MD5

DESCRIPTION

man

man/K.MixPois.Rd
man/SM.MAP.MixReparametrized.Rd
man/Ultimixt-package.Rd
man/SM.MixPois.Rd
man/Plot.MixReparametrized.Rd
man/SM.MixReparametrized.Rd
man/K.MixReparametrized.Rd
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