The package builds a dendrogram for subjects and variables with log posterior of a simple linear model. After data are grouped the Bayes Factor of a mixture versus a single component is given as an importance measure. Model hyperparameters are needed to be given or estimated from data to apply the algorithm.

Author | Vahid PARTOVI NIA |

Date of publication | 2014-11-24 23:57:13 |

Maintainer | Vahid PARTOVI NIA <partovi@math.mcgill.ca> |

License | GPL (>= 2) |

Version | 1.0 |

baybi/DESCRIPTION

baybi/NAMESPACE

baybi/R

baybi/R/baybiclust.R
baybi/R/zzz.R
baybi/data

baybi/data/julien.rda

baybi/man

baybi/man/baybiclust.Rd
baybi/man/baybiplot.Rd
baybi/src

baybi/src/Makevars

baybi/src/cbaybi.c

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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