p: Numeric G$$x$$K matrix of component-specific support parameters.
ref_order: Numeric G$$x$$K matrix of component-specific reference orders.
weights: Numeric vector of G mixture weights.
pi_inv: An object of class top_ordering, collecting the numeric N$$x$$K data matrix of partial orderings, or an object that can be coerced with as.top_ordering.
Returns
Either the likelihood or the log-likelihood value of the Plackett-Luce mixture model parameters for a partial ordering dataset.
Details
The ref_order argument accommodates for the more general mixture of Extended Plackett-Luce models (EPL), involving the additional reference order parameters (Mollica and Tardella 2014). A permutation of the first K integers can be specified in each row of the ref_order argument. Since the Plackett-Luce model is a special instance of the EPL with the reference order equal to the identity permutation, the ref_order argument must be a matrix with G rows equal to (1,…,K) when dealing with Plackett-Luce mixtures.
Mollica, C. and Tardella, L. (2017). Bayesian Plackett-Luce mixture models for partially ranked data. Psychometrika, 82 (2), pages 442--458, ISSN: 0033-3123, DOI: 10.1007/s11336-016-9530-0.
Mollica, C. and Tardella, L. (2014). Epitope profiling via mixture modeling for ranked data. Statistics in Medicine, 33 (21), pages 3738--3758, ISSN: 0277-6715, DOI: 10.1002/sim.6224.