# calcEntropy: Calculates the Entropy of a Given Classification In bayesMCClust: Mixtures-of-Experts Markov Chain Clustering and Dirichlet Multinomial Clustering

## Description

Calculates the entropy of a given classification based on the outcome of a specificed MCMC run of either `mcClust`, `mcClustExtended`, `dmClust` or `dmClustExtended` as well as `MNLAuxMix`.

## Usage

 ```1 2 3``` ```calcEntropy(outList, classProbs, class, grLabels = paste("Group", 1:outList\$Prior\$H), printXtable = TRUE) ```

## Arguments

 `outList` specifies a list containing the outcome (return value) of an MCMC run of `mcClust`, `dmClust`, `mcClustExtended`, `dmClustExtended` or `MNLAuxMix`. `classProbs` A matrix with dimension N x H containing the individual posterior classification probabilities returned by `calcAllocations`. `class` A vector of length N containing the group membership returned by `calcAllocations`. `grLabels` A character vector giving user-specified names for the clusters/groups. `printXtable` If `TRUE` (default) a LaTeX-style table of the entropy is generated.

## Value

A matrix of dimension (H+1) x 3, where H is the number of clusters/groups, containing the contribution of each cluster/group to the (total) entropy – absolute and relative to group size (number of group members). The calculation of the entropy is based on the individual posterior classification probabilities.

## Note

Note, that in contrast to the literature (see References), the numbering (labelling) of the states of the categorical outcome variable (time series) in this package is sometimes 0,...,K (instead of 1,...,K), however, there are K+1 categories (states)!

## Author(s)

Christoph Pamminger <[email protected]>

## References

Sylvia Fruehwirth-Schnatter, Christoph Pamminger, Andrea Weber and Rudolf Winter-Ebmer, (2011), "Labor market entry and earnings dynamics: Bayesian inference using mixtures-of-experts Markov chain clustering". Journal of Applied Econometrics. DOI: 10.1002/jae.1249 http://onlinelibrary.wiley.com/doi/10.1002/jae.1249/abstract

Christoph Pamminger and Sylvia Fruehwirth-Schnatter, (2010), "Model-based Clustering of Categorical Time Series". Bayesian Analysis, Vol. 5, No. 2, pp. 345-368. DOI: 10.1214/10-BA606 http://ba.stat.cmu.edu/journal/2010/vol05/issue02/pamminger.pdf

`calcAllocations`, `mcClust`, `dmClust`, `mcClustExtended`, `dmClustExtended`, `MNLAuxMix`
 ```1 2``` ```# please run the examples in mcClust, dmClust, mcClustExtended, # dmClustExtended, MNLAuxMix ```