| reduceTraj {kmlShape} | R Documentation |
This function 'summerize' a (big) population in a smaller groups of
individual, then simplify the trajectories by reducing their number of
points. It use reduceNbId and
reduceNbTimes. Main difference with these two function,
its applies on a Clds object.
reduceTraj(myClds, nbSenators = NA, nbTimes = NA, spar = 0.5, imputationMethod = "linearInterpol")
myClds |
[ |
nbSenators |
[ |
nbTimes |
[ |
spar |
[ |
imputationMethod |
[ |
This function 'summerize' a (big) population in a smaller groups of
individual, then simplify the trajectories by reducing their number of
points. If 'nbSenators' is not NA, then reduceNbId is
called. If 'nbTimes' is not NA, then reduceNbTimes is
called. Note that 'nbSenators' and 'nbTimes' should not be both
missing.
If both are non-missing, reduceNbId is called first.
The results is store in the field 'senators' of the Clds object.
A Clds object in which the fields
'senators', 'mySenators' and 'senatorsWeight' are now filled.
### Generating artificial data
nbLignes <- 200
trajG <- matrix(0,nbLignes,51)
for(i in 1:(nbLignes/2)){
trajG[i,] <- dnorm(0:50,runif(1,15,35),5)*rnorm(1,10,0.1)
}
for(i in (nbLignes/2+1):nbLignes){
trajG[i,] <- dnorm(0:50,runif(1,15,35),5)*rnorm(1,5,0.1)
}
myClds <- cldsWide(data.frame(1:200,trajG))
plot(myClds)
### Reducing the number of time measurement
reduceTraj(myClds,nbTimes=7)
plotSenators(myClds)
### Reducing the number of individual
reduceTraj(myClds,nbSenators=32)
plotSenators(myClds)
### Reducing both
reduceTraj(myClds,nbSenators=32,nbTimes=7)
plotSenators(myClds)