This class contains the parameters in the output after running classification.

- tik
a matrix of size (number of Curves) x (K), each column contains the weights of the curves in the corresponding class.

- cls
a vector of size number of curves, containing the index of the class for each curve.

- proportion
a matrix of size 1xnbClust (number of clusters), containing the estimated mixture proportions.

- loglikelihood
the estimated log-likelihood.

- aic
the value of AIC criterion.

- bic
the value of BIC criterion.

- icl
the value of ICL criterion.

- dimensions
a vector of size nbClust of the dimensions of the specifique dimensions of the functional data in each class.

- dimTotal
a matrix of size nbClust x nbRunIteration, where nbRunIteration is the number of iterations before the algorithm converge. Each column of the dimTotal matrix contain the dimensions on the coresponding iteration.

- V
principal components variances per cluster

- empty
logical parameter, and empty=TRUE if we have an empty class

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