predict.relaxo

object

 A data frame or matrix containing new data. If not given, the prediction for the original training data is returned. 

newX

 The penalty parameter for variable selection. 

lambda

 The relaxation parameter in the interval [0,1].  

 models

Relaxed Lasso is a generalisation of the Lasso shrinkage
technique for linear regression. Both variable selection and
parameter estimation is achieved by regular Lasso, yet both
steps do not necessarily use the same penalty parameter. The
results include all standard Lasso solutions but allow often
for sparser models while having similar or even slightly better
predictive performance if many predictor variables are present.
The package depends on the LARS package.

predict.relaxo: predict method for class relaxo

Description

Usage

Arguments

Value

References