PLMIX: Bayesian Analysis of Finite Mixture of Plackett-Luce Models

Description Usage Arguments Details Value Author(s) Examples

Return complete rankings/orderings from partial sequences relying on a random generation of the missing positions/items.

make_complete(
  data,
  format_input,
  nranked = NULL,
  probitems = rep(1, ncol(data))
)

`data`	Numeric NxK data matrix of partial sequences to be completed.
`format_input`	Character string indicating the format of the `data` input, namely `"ordering"` or `"ranking"`.
`nranked`	Optional numeric vector of length N with the number of items ranked by each sample unit.
`probitems`	Numeric vector with the K item-specific probabilities to be employed for the random generation of the missing positions/items (see 'Details'). Default is equal probabilities.

The completion of the partial top rankings/orderings is performed according to the Plackett-Luce scheme, that is, with a sampling without replacement of the not-ranked items by using the positive values in the probitems argument as support parameters (normalization is not necessary).

A list of two named objects:

`completedata`	Numeric NxK data matrix of complete sequences with the same format of the input `data`.
`nranked`	Numeric vector of length N with the number of items ranked by each sample unit of the input `data`.

Cristina Mollica and Luca Tardella

## Completion based on the top item frequencies
data(d_dublinwest)
head(d_dublinwest)
top_item_freq <- rank_summaries(data=d_dublinwest, format_input="ordering", mean_rank=FALSE, 
                                pc=FALSE)$marginals["Rank_1",]

d_dublinwest_compl <- make_complete(data=d_dublinwest, format_input="ordering", 
                                    probitems=top_item_freq)
head(d_dublinwest_compl$completedata)