~ Class: ClusterLongData ~
ClusterLongData is an object containing trajectories and associated Partition
When created, an ClusterLongData object simply contains initial
data (the trajectories). After the execution of kml, it
contains
the original data and the Partition which has
just been calculated by kml.
Note that if kml is executed several times, every new Partition
is added to the original ones, no pre-existing Partition is erased.
idAll[vector(character)]: Single identifier
for each of the trajectory (each individual). Usefull for exporting clusters.
idFewNA[vector(character)]: Restriction of
idAll to the trajectories that does not have 'too many' missing
value. See maxNA for details.
time[numeric]: Time at which measures are made.
varNames[character]: Name of the variable measured.
traj[matrix(numeric)]: Contains
the longitudianl data. Each lines is the trajectories of an
individual. Each column is the time at which measures
are made.
dimTraj[vector2(numeric)]: size of the matrix
traj (ie dimTraj=c(length(idFewNA),length(time))).
maxNA[numeric] or [vector(numeric)]:
Individual whose trajectories contain 'too many' missing value
are exclude from traj and will no be use in
the analysis. Their identifier is preserved in idAll but
not in idFewNA. 'too many' is define by maxNA: a
trajectory with more missing than maxNA is exclude.
reverse[matrix(numeric)]: if the trajectories
are scale using the function scale, the 'scaling
parameters' (probably mean and standard deviation) are saved in
reverse. This is usefull to restaure the original data after a
scaling operation.
criterionActif[character]: Store the criterion name that will be used by functions that need a single criterion (like plotCriterion or ordered).
initializationMethod[vector(chararcter)]: list all
the initialization method that has already been used to find some
Partition
(usefull to not run several time a deterministic method).
sorted[logical]: are the Partition
curently hold in the object sorted in decreasing order ?
c1[list(Partition)]: list of
Partition with 1 clusters.
c2[list(Partition)]: list of
Partition with 2 clusters.
c3[list(Partition)]: list of
Partition with 3 clusters.
...c26[list(Partition)]: list of
Partition with 26 clusters.
Class LongData, directly.
Class ListPartition, directly.
Class ClusterizLongData objects can be constructed via function
clusterLongData that turn a data.frame or a matrix
into a ClusterLongData. Note that some artificial data can be
generated using gald.
object['xxx']Get the value of the field
xxx. Inherit from LongData and
ListPartition.
object['xxx']<-valueSet the field xxx to value.
xxx. Inherit from ListPartition.
plotDisplay the
ClusterLongData according to a Partition.
Special thanks to Boris Hejblum for debugging the '[' and '[<-' operators (the previous version was not compatible with the matrix package, which is used by lme4).
Overview: kml-package
Classes : Partition, LongData, ListPartition
Methods : clusterLongData, kml, choice
Plot : plot(ClusterLongData),
plotCriterion
################
### Creation of some trajectories
traj <- matrix(c(1,2,3,1,4, 3,6,1,8,10, 1,2,1,3,2, 4,2,5,6,3, 4,3,4,4,4, 7,6,5,5,4),6)
myCld <- clusterLongData(
traj=traj,
idAll=as.character(c(100,102,103,109,115,123)),
time=c(1,2,4,8,15),
varNames="P",
maxNA=3
)
################
### get and set
myCld["idAll"]
myCld["varNames"]
myCld["traj"]
################
### Creation of a Partition
part2 <- partition(clusters=rep(1:2,3),myCld)
part3 <- partition(clusters=rep(1:3,2),myCld)
################
### Adding a clusterization to a clusterizLongData
myCld["add"] <- part2
myCld["add"] <- part3
myCldPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.