Description Usage Arguments Details Author References See Also Examples
Plot the LongData
or LongData3d
optionnaly relatively
to a Partition
. For joint trajectories, one
graphe for each variable trajectory is displayed.
1 | plotTrajMeans(x, y, parTraj=parTRAJ(), parMean=parMEAN(),...)
|
x |
|
y |
|
parTraj |
|
parMean |
|
... |
Arguments to be passed to methods, such as graphical parameters. |
Plot either a LongData
,
or each variable of a LongData3d
optionnaly according to the Partition
define by y
.
Graphical option concerning the individual trajectory (col, type, pch
and xlab) can be change using parTraj
.
Graphical option concerning the cluster mean trajectory (col, type, pch,
pchPeriod and cex) can be change using parMean
. For more
detail on parTraj
and parMean
, see object of
class ParLongData
.
Christophe Genolini
1. UMR U1027, INSERM, Universit<e9> Paul Sabatier / Toulouse III / France
2. CeRSM, EA 2931, UFR STAPS, Universit<e9> de Paris Ouest-Nanterre-La D<e9>fense / Nanterre / France
[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
LongData
, LongData3d
, plotTrajMeans3d
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | ##################
### Construction of the data
data(artificialLongData)
ld <- longData(artificialJointLongData)
part <- partition(rep(1:3,each=50))
### Basic plotting
plotTrajMeans(ld)
plotTrajMeans(ld,part,xlab="Time")
##################
### Changing graphical parameters 'par'
### No letters on the mean trajectories
plotTrajMeans(ld,part,parMean=parMEAN(type="l"))
### Only one letter on the mean trajectories
plotTrajMeans(ld,part,parMean=parMEAN(pchPeriod=Inf))
### Color individual according to its clusters (col="clusters")
plotTrajMeans(ld,part,parTraj=parTRAJ(col="clusters"))
### Mean without individual
plotTrajMeans(ld,part,parTraj=parTRAJ(type="n"))
### No mean trajectories (type="n")
### Color individual according to its clusters (col="clusters")
plotTrajMeans(ld,part,parTraj=parTRAJ(col="clusters"),parMean=parMEAN(type="n"))
### Only few trajectories
plotTrajMeans(ld,part,nbSample=10,parTraj=parTRAJ(col='clusters'),parMean=parMEAN(type="n"))
##################
### single variable trajectory
data(artificialLongData)
ld2 <- longData(artificialLongData)
part2 <- partition(rep(1:4,each=50))
plotTrajMeans(ld2)
plotTrajMeans(ld2,part2)
|