plotTrajMeans3d: ~ Function: plotTrajMeans3d for LongData3d ~
In longitudinalData: Longitudinal Data

plotTrajMeans3d,LongData

R Documentation

~ Function: plotTrajMeans3d for LongData3d ~

Description

Plot two variables of a LongData3d object in 3D, optionnaly relatively to a Partition.

Usage

plotTrajMeans3d(x,y,varY=1,varZ=2,
   parTraj=parTRAJ(),parMean=parMEAN(type="n"),...)

Arguments

`x`	`[LongData3d]`: Object containing the trajectories to plot.
`y`	`[Partition]`: `Partition` that will be use to plot the object. If `y` is missing, a `Partition` with a single clusters is considered.
`varY`	`[numeric]` or `[character]`: either the number or the name of the first variable to display. 1 by default.
`varZ`	`[numeric]` or `[character]`: either the number or the name of the second variable to display. 2 by default.
`parTraj`	`[parLongData]`: Set the graphical parameters used to plot the trajectories of the `LongData3d`. See `ParLongData` and examples for details.
`parMean`	`[parLongData]`: Set the graphical parameters used to plot the mean trajectories of each clusters `LongData3d` (only when `y` is non missing). See `ParLongData` and examples for details.

...

Arguments to be passed to methods, such as graphical parameters.

Details

Plot two variables of a LongData3d object in 3D. It use the rgl library. The user can make the graphical representation turn using the mouse.

Author

Christophe Genolini
1. UMR U1027, INSERM, Universit<e9> Paul Sabatier / Toulouse III / France
2. CeRSME, EA 2931, UFR STAPS, Universit<e9> de Paris Ouest-Nanterre-La D<e9>fense / 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

Examples


##################
### Construction of the data


time=c(1,2,3,4,8,12,16,20)
id2=1:120
f <- function(id,t)((id-1)%%3-1) * t
g <- function(id,t)(id%%2+1)*t
h <- function(id,t)(id%%4-0.5)*(20-t)
ld <- longData3d(array(cbind(outer(id2,time,f),outer(id2,time,g),outer(id2,time,h))+
   rnorm(120*8*3,0,3),dim=c(120,8,3)))
part <- partition(rep(1:6,20))

### Basic plotting
plotTrajMeans3d(ld)
plotTrajMeans3d(ld,part)

### Variable 1 and 3, then 2 and 3
plotTrajMeans3d(ld,part)
plotTrajMeans3d(ld,part,varY=3,varZ=2)
plotTrajMeans3d(ld,part,varY=1,varZ=3)

##################
### Changing graphical parameters 'par'

### Color individual according to its clusters (col="clusters")
plotTrajMeans3d(ld,part,parTraj=parTRAJ(col="clusters"))
plotTrajMeans3d(ld,part,parTraj=parTRAJ(col="clusters"),varY=1,varZ=3)

### No mean trajectories (type="n"), only few trajectories
### Color individual according to its clusters (col="clusters")
plotTrajMeans3d(ld,part,parTraj=parTRAJ(col="clusters"),parMean=parMEAN(type="n"),nbSample=10)

longitudinalData documentation built on Feb. 16, 2023, 9:54 p.m.