Description Usage Arguments Value Author(s) Examples
This function estimates the loglikelihood of a mixture of multidimensional ISR model, as well as the BIC and ICL model selection criteria.
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data |
a matrix in which each row is a rank (partial or not; for partial rank, missing elements of a rank are put to 0 ). |
proportion |
a vector (which sums to 1) containing the K mixture proportions. |
pi |
a matrix of size K*p, where K is the number of clusters and p the number of dimension, containing the probabilities of a good comparaison of the model (dispersion parameters). |
mu |
a matrix of size K*sum(m), containing the modal ranks. Each row contains the modal rank for a cluster. In the case of multivariate ranks, the reference rank for each dimension are set successively on the same row. |
m |
a vector containing the size of ranks for each dimension. |
Ql |
number of iterations of the Gibbs sampler used for the estimation of the log-likelihood. |
Bl |
burn-in period of the Gibbs sampler. |
IC |
number of run of the computation of the loglikelihood. |
nb_cpus |
number of cpus for parallel computation |
a list containing:
ll |
the estimated log-likelihood. |
bic |
the estimated BIC criterion. |
icl |
the estimated ICL criterion. |
Quentin Grimonprez
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