predict.LarsPath: Prediction of response
In HDPenReg: High-Dimensional Penalized Regression

Description Usage Arguments Value Author(s) Examples

Predict response of a new sample Xnew at a given level of penalty

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## S3 method for class 'LarsPath'
predict(object, Xnew, lambda, mode = c("fraction",
  "lambda", "norm"), ...)

`object`	a LarsParth object
`Xnew`	a matrix (of size n*object@p) of covariates.
`lambda`	If mode ="norm", lambda represents the l1-norm of the coefficients with which we want to predict. If mode="fraction", lambda represents the ratio (l1-norm of the coefficientswith which we want to predict)/(l1-norm maximal of the LarsPath object).
`mode`	"fraction", "lambda" or "norm".
`...`	other arguments. Not used.

The predicted response

Quentin Grimonprez

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dataset=simul(50,10000,0.4,10,50,matrix(c(0.1,0.8,0.02,0.02),nrow=2))
result=HDlars(dataset$data[1:40,],dataset$response[1:40])
y=predict(result,dataset$data[41:50,],0.3,"fraction")