ClusterWithMeanCurve: Mean Cluster Curves
In mbeccuti/Prova:

Selecting a model among FCM, Malthus, Gompertz and Logistic model, MClusterWithMeanCurve() generates the mean cluster curves in a single plot and in a plot per each cluster the curves that belongs to that. Furthemore it saves all the principal informations about that clusterization, for instance mean curve values and the cluster of belonging per each curve.

1	ClusterWithMeanCurve(out.funcit, databaseTr, k, model, feature)

`out.funcit`	Object of class funcyOutList, obtained by the function funcit from the package "funcy" or, selecting a value for k (number of clusters) and h (dimension of the space of of the cluster mean), from the function cluster_choice.
`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.
`k`	Number of clusters.
`model`	String model name, it is possible to choose one among FCM, Malthus, Gompertz and Logistic models.
`feature`	String feature name, stored in the target file, to plot curves according to.

List containing the cluster mean curves plot for the model choosen, the k growth curves plots divided depending on the cluster and a list of informations about the model clustered. The information list stores the mean cluster.

mbeccuti/Prova documentation built on May 20, 2019, 5:26 p.m.