loglikelihood function

Likelihood and log-likelihood evaluation for a mixture of Plackett-Luce models

Likelihood and log-likelihood evaluation for a mixture of Plackett-Luce models

Compute either the likelihood or the log-likelihood of the Plackett-Luce mixture model parameters for a partial ordering dataset.

likPLMIX(p, ref_order, weights, pi_inv) loglikPLMIX(p, ref_order, weights, pi_inv)

Arguments

  • 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 GG 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 KK 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 GG rows equal to (1,,K)(1,\dots,K) when dealing with Plackett-Luce mixtures.

Examples

data(d_apa) K <- ncol(d_apa) G <- 3 support_par <- matrix(1:(G*K), nrow=G, ncol=K) weights_par <- c(0.50, 0.25, 0.25) loglikPLMIX(p=support_par, ref_order=matrix(1:K, nrow=G, ncol=K, byrow=TRUE), weights=weights_par, pi_inv=d_apa)

References

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.

Author(s)

Cristina Mollica and Luca Tardella

  • Maintainer: Cristina Mollica
  • License: GPL (>= 2)
  • Last published: 2019-09-04

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