A generic reference Bayesian analysis of unidimensional mixtures of Gaussian distributions obtained by a location-scale parameterisation of the model is implemented. Included functions can be applied to produce a Bayesian analysis of Gaussian mixtures with an arbitrary number of components, with no need to define the prior distribution.

Author | Kaniav Kamary, Kate Lee |

Date of publication | 2015-12-18 06:43:04 |

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

License | GPL (>= 2.0) |

Version | 2.0 |

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

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

Ultimixt

Ultimixt/NAMESPACE

Ultimixt/R

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

Ultimixt/DESCRIPTION

Ultimixt/man

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