RankDistanceModel function

Fit A Mixture of Distance-based Models

RankDistanceModel fits ranking models based on inputs

RankDistanceModel(dat, init, ctrl)

Arguments

• dat: A RankData object.
• init: A RankInit object.
• ctrl: A RankControl object.

Returns

A list containing the following components:

• modal_ranking.est: the estimated modal ranking for each cluster.
• p: the marginal probability of each cluster.
• w.est: the estimated weights of each cluster.
• param.est: the phi parametrisation of weights of each cluster (for Weighted Kendall model only).
• 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

Details

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

See Also

RankData, RankInit, RankControl