FittingAndClustering: Fitting and Clustering
In mbeccuti/Prova:

Using the function ClusterWithMeanCurve() it is possible to save the mean cluster curves in a single plot and in a plot per each cluster the curves that belongs to that. With FittingAndClustering() is possible to do that for the FCM, Malthus, Gompertz and Logistic models in order to compare their clusterizations. These plots could be saved in a pdf per each model, furthermore it saves in a single pdf (MeanCurves.pdf) the mean cluster curves for all the models.

1 2	FittingAndClustering(databaseTr, h, k, FCM_all, feature, save = FALSE, path = NULL)

`databaseTr`	List containing the number of observations per each curve (called LenCurv), and a data frame constituted from the curves' ID, observed values and the respective times, that might be truncated at a specific time or not. It is generated automatically from the function DataImport() or DataTruncation() if we want consider a truncation time.
`h`	Dimension of the cluster mean space.
`k`	Number of clusters, it could be a vector.
`FCM_all`	List of the all funcit's outputs for each k and h obtained from the function "cluster_choice".
`feature`	String feature name, stored in the target file, to plot curves according to.
`save`	When TRUE (the default is FALSE), it is possible to save the plots of the growth curves divided depending on the belonging cluster in a pdf per each model.
`path`	Path to save plot to (combined with filename).