Builds a dendrogram using log posterior as a natural distance defined by the model and meanwhile waits the clustering variables. It is also capable to computing equivalent Bayesian discrimination probabilities. The adopted method suites small sample large dimension setting. The model parameter estimation maybe difficult, depending on data structure and the chosen distribution family.

Author | Vahid PARTOVI NIA and Anthony C. DAVISON |

Date of publication | 2015-08-27 17:06:01 |

Maintainer | Vahid PARTOVI NIA <vpartovinia@gmail.com> |

License | GPL (>= 2) |

Version | 1.5 |

http://bclust.r-forge.r-project.org/ |

**bclust:** Bayesian agglomerative clustering for high dimensional data...

**bclustvs:** bclustvs (Bayesian CLUSTering with Variable Selection) is a...

**bdiscrim:** discrimination using a Bayesian linear model

**ditplot:** dendrogram-image-teeth plot

**dptplot:** dendrogram-profile-teeth plot

**gaelle:** Messerli et. al. metabolomic data

**imp:** calculates variable and variable-cluster importances

**loglikelihood:** computes the model log likelihood useful for estimation of...

**meancss:** computes statistics necessary for the evaluation of the log...

**profileplot:** a plot useful to visualise replicated data

**teethplot:** produces teeth plot useful for demonstating a grouping on...

**viplot:** variable importance plot

bclust/DESCRIPTION

bclust/NAMESPACE

bclust/R

bclust/R/bclust.R
bclust/R/zzz.R
bclust/data

bclust/data/gaelle.rda

bclust/inst

bclust/inst/CITATION

bclust/man

bclust/man/bclust.Rd
bclust/man/bclustvs.Rd
bclust/man/bdiscrim.Rd
bclust/man/ditplot.Rd
bclust/man/dptplot.Rd
bclust/man/gaelle.Rd
bclust/man/imp.Rd
bclust/man/loglikelihood.Rd
bclust/man/meancss.Rd
bclust/man/profileplot.Rd
bclust/man/teethplot.Rd
bclust/man/viplot.Rd
bclust/src

bclust/src/ClusteringvsGAL05.c

bclust/src/Makevars

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

All documentation is copyright its authors; we didn't write any of that.