make_complete: Completion of partial rankings/orderings

In PLMIX: Bayesian Analysis of Finite Mixtures of Plackett-Luce Models for Partial Rankings/Orderings

Description

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

Usage

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

Arguments

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.

Details

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).

Value

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.

Author(s)

Cristina Mollica and Luca Tardella

Examples

## 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)

PLMIX documentation built on Sept. 4, 2019, 5:03 p.m.