resB: Representation of the predicted vs observed behaviour of an...
In ldbk/m2b: Movement to Behaviour Inference using Random Forest

Description Usage Arguments Value Author(s) See Also Examples

Representation of the predicted vs observed behaviour of an xytb object

1	resB(xytb, type = "time", nob = "-1")

`xytb`	an xytb object with predicted behaviour.
`type`	`time`: plot results in time. `space`: plot results in space. `density`: plot results in space, adding density surface by behaviour.
`nob`	character. Define the unobserved value of the behaviour (and where prediction are done)

a ggplot

Laurent Dubroca

See randomForest

## Not run: 
#track_CAGA_005 is dataset
#generate a complete xytb object with derived (over moving windows of 3, 5
#and 9 points, with quantile at 0, 50 and 100%) and shifted information on 10
#and 100 points
xytb<-xytb(track_CAGA_005,"a track",c(3,5,9),c(0,.5,1),c(10,100))
#compute a random forest model to predict behaviour (b, where -1 is
#unobserved behaviour) using the derived
#parameters ("actual")
xytb<-modelRF(xytb,"actual",nob="-1",colin=TRUE,varkeep=c("v","thetarel"),
zerovar=TRUE,rfcv=FALSE,step=.9)
#behaviour results:
resB(xytb,type="time",nob="-1")
resB(xytb,type="space",nob="-1")
resB(xytb,type="density",nob="-1")

## End(Not run)