RankDistanceModel: Fit A Mixture of Distance-based Models
In simonfqy/rankdistext:

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

simonfqy/rankdistext documentation built on May 29, 2019, 8:19 p.m.

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