# Calculates Posterior Expectations, Standard Deviations and (Optionally) HPD Intervals for the MNL Regression Coefficients

### Description

Calculates posterior expectations, standard deviations and (optional) highest probability density (HPD) intervals
for the multinomial logit (MNL) regression coefficients (using `boa.hpd`

from package boa)
and also offers some other analyses like plotting paths and autocorrelation functions (ACFs) for the corresponding
MCMC draws.

### Usage

1 2 3 | ```
calcRegCoeffs(outList, hBase = 1, thin = 1, M0 = outList$Mcmc$M0,
grLabels = paste("Group", 1:outList$Prior$H),
printHPD = TRUE, plotPaths = TRUE, plotACFs = TRUE)
``` |

### Arguments

`outList` |
specifies a list containing the outcome (return value) of an MCMC run of |

`hBase` |
specifies the cluster/group which should serve as |

`thin` |
An integer specifying the thinning parameter (default is 1). |

`M0` |
specifies the number of the first MCMC draw after burn-in (default is |

`grLabels` |
A character vector giving user-specified names for the clusters/groups. |

`printHPD` |
If |

`plotPaths` |
If |

`plotACFs` |
If |

### Value

A list containing:

`[[h]], h=1,..,H ` |
A matrix containing posterior expectation ( |

`regCoeffsAll ` |
A matrix containing posterior expectation ( |

### 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 <christoph.pamminger@gmail.com>

### 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

### See Also

`boa.hpd`

, `acf`

, `mcClustExtended`

, `dmClustExtended`

,
`MNLAuxMix`

### Examples

1 2 | ```
# please run the examples in mcClustExtended, dmClustExtended and
# MNLAuxMix
``` |