PLMIX: summary.mpPLMIX – R documentation

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summary.mpPLMIX

Summary of the MAP estimation for a Bayesian mixture of Plackett-Luce models

Description

summary method for class mpPLMIX. It provides summaries for the MAP estimation of a Bayesian mixture of Plackett-Luce models.

Usage

## S3 method for class 'mpPLMIX'
summary(object, digits = 2, ...)

Arguments

`object`	Object of class `mpPLMIX` returned by the `mapPLMIX` or `mapPLMIX_multistart` function.
`digits`	Number of decimal places for rounding the summaries.
`...`	Further arguments passed to or from other methods (not used).

Value

A list of summaries for the mpPLMIX class object:

`MAP_w`	Numeric vector with the MAP estimates of the G mixture weights. Returned only when when G>1.
`MAP_p`	Numeric GxK matrix with the MAP estimates of the component-specific support parameters.
`MAP_modal_orderings`	Numeric GxK matrix with the estimated modal orderings of each mixture component.
`group_distr`	Numeric vector with the relative frequency distribution of the mixture component memberships based on MAP allocation. Returned only when when G>1.
`perc_conv_rate`	Numeric scalar with the percentage of MAP algorithm convergence over the multiple starting points. Returned only when `summary.mpPLMIX` is applied to the output of the `mapPLMIX_multistart` function.

Author(s)

Cristina Mollica and Luca Tardella

Examples

## Summary of the MAP procedure with a single starting point
data(d_carconf)
MAP <- mapPLMIX(pi_inv=d_carconf, K=ncol(d_carconf), G=3)
summary(MAP)

## Summary of the MAP procedure with 5 starting points
MAP_multi <- mapPLMIX_multistart(pi_inv=d_carconf, K=ncol(d_carconf), G=3, n_start=5)
summary(MAP_multi)

PLMIX

Bayesian Analysis of Finite Mixtures of Plackett-Luce Models for Partial Rankings/Orderings

v2.1.1

GPL (>= 2)

Authors

Cristina Mollica [aut, cre], Luca Tardella [aut]

Initial release

2019-09-04