Description Usage Arguments Details Value

`RankDistModel`

fits a mixture of ranking models based on weighted Kendall distance.

1 | ```
RankDistanceModel(dat, init, ctrl)
``` |

`dat` |
A RankData object. |

`init` |
A RankInit object. |

`ctrl` |
A RankControl object. |

The procedure will estimate central rankings, the probability of each cluster and weights.

A list containing the following components:

`modal_ranking.est`

the estimated pi0 for each cluster.

`p`

the probability of each cluster.

`w.est`

the estimated weights of each cluster.

`alpha`

the estimated alpha for each cluster.

`param.est`

the param parametrisation of weights of each cluster.

`SSR`

the sum of squares of Pearson residuals

`log_likelihood`

the fitted log_likelihood

`BIC`

the fitted Bayesian Information Criterion value

`free_params`

the number of free parameters in the model

`expectation`

the expected value of each observation given by the model

`iteration`

the number of EM iteration

`model.call`

the function call

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