predict.ic.glmnet: Predict method for ic.glmnet objects

In tboonman/eba_lasso_bma: Implementation of several econometric models in high-dimension.

Description

Predicted values based on ic.glmnet object.

Usage

## S3 method for class 'ic.glmnet'
predict(object, newdata, ...)

Arguments

object	A ic.glmnet 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.

Examples

## == 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 the data into in-sample and out-of-sample
y.in=y[1:100]; y.out=y[-c(1:100)]
x.in=x[1:100,]; x.out=x[-c(1:100),]

## == LASSO == ##
lasso=ic.glmnet(x.in,y.in,crit = "bic")

pred=predict(lasso,newdata=x.out)
plot(y.out, type="l")
lines(pred, col=2)

tboonman/eba_lasso_bma documentation built on Nov. 5, 2019, 10:01 a.m.