Description Usage Arguments Value Author(s) References See Also

View source: R/mixturetarget.R

Create the posterior distribution of the parameters of a mixture of univariate gaussian distributions, with a fixed (known) number of components.

1 | ```
createMixtureTarget(mixturesample, mixturesize, ncomponents, mixtureparameters)
``` |

All the arguments are optional, since if none is given, a mixture distribution with 4 components will be created, as in Jasra, Holmes, Stephens, "MCMC and label switching problem in Bayesian mixture models", published in Statistical Science (2005).

`mixturesample` |
Object of class |

`mixturesize` |
Object of class |

`ncomponents` |
Object of class |

`mixtureparameters` |
Object of class |

The function returns an object of class `target-class`

, with a name, a dimension, a function giving the log density,
a function to generate sample from the distribution, parameters of the distribution, and a function to draw init points for
the MCMC algorithms. The log density involves a likelihood and a prior, and the prior is as in Richardson and Green, "On Bayesian
analysis of mixtures with an unknown number of components", published in JRSS B, 1997.

Luke Bornn <bornn@stat.harvard.edu>, Pierre E. Jacob <pierre.jacob.work@gmail.com>

Jasra, Holmes, Stephens, "MCMC and label switching problem in Bayesian mixture models", published in Statistical Science (2005). Richardson and Green, "On Bayesian analysis of mixtures with an unknown number of components", published in JRSS B, 1997.

`target-class`

, `createTrimodalTarget`

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