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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