clusterizLongData {kml} | R Documentation |
clusterizLongData
(or cld
in short) is the constructor
for ClusterizLongData
object.
clusterizLongData(traj, id, time, varName = "V", trajSizeMin = 1) cld(traj, id, time, varName = "V", trajSizeMin = 1)
traj |
[array(numeric)] : contains longitudinal
data. Each line is the trajectory of an individual. The columns refer to the time during which measures were made. |
id |
[character] : single identifier
for each individual (i.e. each trajectories). Note that the identifiant are of type
character (that allow to deal identifiants like XUK32-612
identifiant that our favorite epidemiologists are so good at providing) . If numeric are provided, they are converted into characters . |
time |
[numeric] : time during which measures were made. |
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. For example, if the trajectories have 7 mesurements
(time=7 ) and trajSizeMin is set to 3, the trajectory
(5,3,NA,4,NA,NA,NA) will be include in the calculation while
(2,NA,NA,NA,4,NA,NA) will be exclude. Please note that trajectories
that are totally missing (i.e. 0 present values) are always excluded. |
clusterizLongData
create a
ClusterizLongData
object and set its slot to the
corresponding value. Note that the field clusters
can not be
initialised through this function since this slot is not suppose be be
manipulated by the user (only by kml
).
Object of class ClusterizLongData
.
Christophe M. Genolini
PSIGIAM: Paris Sud Innovation Group in Adolescent Mental Health
INSERM U669 / Maison de Solenn / Paris
Contact author: <genolini@u-paris10.fr>
Raphaël Ricaud
Laboratoire "Sport & Culture" / "Sports & Culture" Laboratory
University of Paris 10 / Nanterre
Article submited
Web site: http://christophe.genolini.free.fr/kml
Overview: kml-package
Classes : ClusterizLongData
Methods : choice
, as.clusterizLongData
Plot : plot: overview
, plot(ClusterizLongData)
,
plotSubGroups(ClusterizLongData)
, plotAll(ClusterizLongData)
mat <- matrix(c(1,2,3,1,4,6,1,8,10),3) (ld1 <- cld(traj=mat,id=c("1","2","3"),time=c(1,2,3),varName="V",trajSizeMin=2)) (ld2 <- clusterizLongData(traj=mat,id=c("A-101","A-102","A-108"),time=c(2,4,8),varName="Age",trajSizeMin=2))