# Bayesthresh: Bayesian thresholds mixed-effects models for categorical data

This package fits a linear mixed model for ordinal categorical responses using Bayesian inference via Monte Carlo Markov Chains. Default is Nandran & Chen algorithm using Gaussian link function and saving just the summaries of the chains. Among the options, package allow for two other options of algorithms, for using Student's "t" link function and for saving the full chains.

- Author
- Fabio Mathias Correa <fmcorrea@uesc.br> and Julio Silvio de Sousa Bueno Filho <juliobuenof@gmail.com>
- Date of publication
- 2013-03-26 12:05:55
- Maintainer
- Fabio Mathias Correa <fmcorrea@uesc.br>
- License
- GPL (>= 2)
- Version
- 2.0.1

## Man pages

- ACGaussian
- Albert and Chib algorithm with Gaussian distribution for...
- ACt
- Albert and Chib algorithm with t-Student distribution for...
- Bayes.factor
- Bayes factor of the two models
- Bayesthresh
- Bayesian thresholds mixed-effects models for categorical data
- coef.Bayesthresh
- Coefficients for the fixed effects model
- compVar
- Variance component estimates
- MCGaussian
- Kizilkaya et. al. (2003) algorithm with Gaussian distribution...
- MCMCsample
- MCMC sample
- MCt
- Kizilkaya et. al. (2003) algorithm using Student's "t"...
- NCGaussian
- Nandram and Chen (1996) algorithm with Gaussian distribution...
- NCt
- Nandram and Chen (1996) algorithm with t-Student distribution...
- plot.random.effects
- Plot random effects of model
- predict.Bayesthresh
- Extract the predict values
- random.effects
- Extract the random effects of the model
- sensory
- Sensory analysis of banana
- summary.Bayesthresh
- Summary