ocomposition: Regression for Rank-Indexed Compositional Data

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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

View on CRAN

Man pages

auxiliary
auxiliary functions
data
Example data
fitcomp
Gibbs sampler for parameter estimation
negbin
Truncated negative binomial distribution function and...
plot.comphat
Plot predicted composition.
predict.composition
Predicted compositional vector
summary.composition
Summary function

Files in this package

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