Regression model where the response variable is a rank-indexed compositional vector (non-negative values that sum up to one and are ordered from the largest to the smallest). Parameters are estimated in the Bayesian framework using MCMC methods.

Author | Arturas Rozenas, New York University |

Date of publication | 2015-08-10 09:09:58 |

Maintainer | Arturas Rozenas <ar199@nyu.edu> |

License | GPL (>= 2) |

Version | 1.1 |

ocomposition

ocomposition/NAMESPACE

ocomposition/data

ocomposition/data/data.rda

ocomposition/R

ocomposition/R/predict.composition.R
ocomposition/R/a.R
ocomposition/R/logit.R
ocomposition/R/v.y.R
ocomposition/R/rmnorm.R
ocomposition/R/cntr.R
ocomposition/R/summary.composition.R
ocomposition/R/y.v.R
ocomposition/R/fitcomp.R
ocomposition/R/dtnegbin.R
ocomposition/R/plot.comphat.R
ocomposition/R/rtnegbin.R
ocomposition/MD5

ocomposition/DESCRIPTION

ocomposition/man

ocomposition/man/predict.composition.Rd
ocomposition/man/auxiliary.Rd
ocomposition/man/summary.composition.Rd
ocomposition/man/plot.comphat.Rd
ocomposition/man/data.Rd
ocomposition/man/fitcomp.Rd
ocomposition/man/negbin.Rd
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