longData3d {longitudinalData}

~ Function: longData3d ~

Description

longData3d is a constructor of the class LongData. It create object LongData containing several joint trajectory (two or more variable-trajectories). For creating a single variable-trajectory, see longData.

Usage

longData3d(traj, idAll, time, timeInData,varNames,maxNA)

Arguments

traj

[array(numeric)] or data.frame: structure containning the variable-trajectories.

idAll

[vector(character)]: single identifier for each trajectory (ie each individual).

time

[vector(numeric)]: time at which measures were made.

timeInData

[list(vector(numeric))]: Precise the column containing the trajectories. If traj is a data.frame, it sould be a list.

varNames

[character]: name of the variable-trajectories being measured.

maxNA

[vector(numeric)]: maximum number of NA that are tolerates on a trajectory (one for each variable). If a trajectory has more missing than maxNA, then it is remove from the analysis.

Details

longData3d construct a object of class LongData. Two cases can be distinguised:

traj is an array:

the first dimension (line) are individual. The second dimension (column) are time at which the measurement are made. The third dimension are the differents variable-trajectories. For example, traj[,,2] is the second variable-trajectory.

If idAll is missing, the individuals are labelled i1, i2, i3,...

If timeInData is missing, all the column are used (1:ncol(traj)).

If traj is a data.frame:

lines are individual. Time of measurement and variables should be provide through timeInData. timeInData is a list. The label of the list are the variable-trajectories names. Elements of the list are the column containning the trajectories. For example, if timeInData=list(V=c(2,3,4),W=c(6,8,12)), then the first variable-trajectory is 'V', its measurement are in column 2,3 and 4. The second variable-trajectory is 'W', its measurement are in column 6,8 and 12.

If idAll is missing, the first column of the data.frame is used.

Value

An object of class LongData.

Author

Christophe Genolini
1. UMR U1027, INSERM, Université Paul Sabatier / Toulouse III / France
2. CeRSME, EA 2931, UFR STAPS, Université de Paris Ouest-Nanterre-La Défense / Nanterre / France

References

[1] C. Genolini and B. Falissard
"KmL: k-means for longitudinal data"
Computational Statistics, vol 25(2), pp 317-328, 2010

[2] C. Genolini and B. Falissard
"KmL: A package to cluster longitudinal data"
Computer Methods and Programs in Biomedicine, 104, pp e112-121, 2011

See Also

LongData

Examples

#################
### From array

mat <- array(c(1,NA,3,2,3,6,1,8,10,1,NA,1,2,NA,3,2,3,2),dim=c(3,3,2))
longData3d(mat)
(ld1 <- longData3d(mat,varNames=c("Hyp","Col"),idAll=c("i101","i104","i105")))
plotTrajMeans3d(ld1)

#################
### From data.frame

dn <- data.frame(id=1:3,v1=c(2,2,1),t1=c(20,21,22),v1=c(3,2,2),t2=c(23,20,28),t3=c(25,24,29))
longData3d(dn,timeInData=list(c(2,4),c(3,5)),varNames=c("V","T"))
(ld3 <- longData3d(dn,timeInData=list(V=c(2,4,NA),T=c(3,5,6))))
plotTrajMeans3d(ld3)