Description Usage Arguments Examples
View source: R/predict.boosting.R
Predicted values based on boosting object.
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object |
A boosting object estimated using the ic.glmnet function. |
newdata |
An optional data to look for the explanatory variables used to predict. If omitted, the fitted values are used. |
... |
Arguments to be passed to other methods. |
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 | ## == This example uses the Brazilian inflation data from
#Garcia, Medeiros and Vasconcelos (2017) == ##
data("BRinf")
## == Data preparation == ##
## == The model is yt = a + Xt-1'b + ut == ##
aux = embed(BRinf,2)
y=aux[,1]
x=aux[,-c(1:ncol(BRinf))]
## == break data (in-sample and out-of-sample)
yin=y[1:120]
yout=y[-c(1:120)]
xin=x[1:120,]
xout=x[-c(1:120),]
## == Use factors == ##
factors=prcomp(xin,scale. = TRUE)
xfact=factors$x[,1:10]
model=boosting(xfact,yin)
xfactout=predict(factors,xout)[,1:10]
pred=predict(model,xfactout)
plot(yout,type="l")
lines(pred,col=2)
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