Hi Dears,
When I introduce an interaciton in a piecewise model I obtain some quite
unusual results.
If that would't take u such a problem I'd really appreciate an advise from
you.
I've reproduced an example below...
Many thanks
x<-rnorm(1000)
y<-exp(-x)+rnorm(1000)
plot(x,y)
abline(v=-1,col=2,lty=2)
mod<-lm(y~x+x*(x>-1))
summary(mod)
yy<-predict(mod)
lines(x[order(x)],yy[order(x)],col=2,lwd=2)
#--lme
#grouping factor, unbalanced
g<-as.character(c(1:200))
id<-sample(g,size=1000,replace=T,
prob=sample(0:1,200,rep=T))
table(id) #unbalanced
mod2<-lme(y~x+x*(x>-1),random=~x|id,
data=data.frame(x,y,id))
summary(mod2)
newframe<-data.frame( #fictious id
id="fictious",
x)
newframe[1:5,]
#predictions
yy2<-predict(mod2,level=0, newdata=newframe)
lines(x[order(x)],yy2[order(x)],col="blue",lwd=2)
# add variable in the model
z<-rgamma(1000,4,6)
mod3<-lme(y~x+x*(x>-1)+z
,random=~x|id,
data=data.frame(x,y,z,id))
summary(mod3)
#new id
newframe2<-data.frame( #fictious id
id="fictious",
x,
z)
#predict
yy3<-predict(mod3,level=0, newdata=newframe2)
lines(x[order(x)],yy3[order(x)],col="green",lwd=2)
# ADD INTERACTION z:x
mod4<-lme(y~x+x*(x>-1)+
z+
z:x+
z:x*(x>-1)
,random=~x|id,
data=data.frame(x,y,z,id))
#predict
yy4<-predict(mod4,level=0, newdata=newframe2)
lines(x[order(x)],yy4[order(x)],col="violet",lwd=2) #something bizarre
#starts to happen
#in the predicted values
# they begin to jiggle around the straight line
--
*Little u can do against ignorance,....it will always disarm u:
is the 2nd principle of thermodinamics made manifest, ...entropy in
expansion.**....But setting order is the real quest 4 truth, ......and the
mission of a (temporally) wise dude.
*
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