| ClusterizLongData-class {kml} | R Documentation |
ClusterizLongData is an objet containing trajectories and associated clusterizations.
KmL is an algorithm that builds an ensemble of Clusterization from longitudinal data. ClusterizLongData
is the object contaning the original longitudinal data, then all the Clusterization that KmL finds.
When created, a class ClusterizLongData object simply contains initial data (the trajectories). After the execution of KmL, it contains
the original data as well as the Clusterization which has just been calculated by the KmL.
Please note that if KmL is executed several times, the new Clusterization
are added to the original ones, no pre-existing Clusterization is erased.
id[character] : single identifier
for each of the trajectories, which is to say each individual.time[numeric]: time during which measures were made.traj[array(numeric)]: contains longitudinal data. Each line corresponds to the trajectory of an individual. The columns refer to the time during which measures were made.
The third dimension enables you to considerer more variables (joint trajetories, actuelly under development)varName[character]:
Name of the variable measured.trajSizeMin[numeric]:
Trajectories whose values are partially missing can either be excluded by treatment, or included. trajSizeMin sets the
minimum number of values that a trajectory must contain not to be excluded. Please note that trajectories
that are totally missing (i.e. 0 present values) must always be excluded.clusterizList:[list(list(Clusterization))]
clusterzList contains the list of Clusterization found by
KmL. More specifically, clusterizList contains nine items : c2, c3,
c4 up to c10. Each item contains a list of Clusterization: c2 contains the Clusterization having 2 clusters, c3
contains the Clusterization having 3 clusters and so on.
Class ClusterizLongData objects can be constructed
via function as.cld. This fonction takes into account matrix (see as.cld.matrix),
data.frame (voir as.cld.data.frame) and ArtificialLongData (see
as.cld.artificialLongData).
signature(.Object = "ClusterizLongData"):
KmL is the algorithm that enables you to construct the new
Clusterization based on longitudinal data contained in .Object.signature(x = "ClusterizLongData"):
choice enables you to display all Clusterization
found, to choose the one that seems fittest and to export its graphic representation.
Christophe M. Genolini
PSIGIAM: Paris Sud Innovation Group in Adolescent Mental Health
INSERM U669 / Maison de Solenn / Paris
Responsable : <genolini@u-paris10.fr>
Raphaël Ricaud
Laboratoire "Sport & Culture" / "Sports & Culture" Laboratory
University of Paris 10 / Nanterre
Article submited at ``Statistics in Medicines''
showClass("ClusterizLongData")