complexity.LASSO: Interface for selection of optimal parameter for lasso fit

In peperr: Parallelised Estimation of Prediction Error

Interface for selection of optimal parameter for lasso fit

Description

Determines the optimal value for tuning parameter lambda for a regression model with lasso penalties via cross-validation. Conforming to the calling convention required by argument complexity in peperr call.

Usage

complexity.LASSO(response, x, full.data, ...)

Arguments

response	a survival object (Surv(time, status)).
x	n*p matrix of covariates.
full.data	data frame containing response and covariates of the full data set.
...	additional arguments passed to optL1 of package penalized call.

Details

Function is basically a wrapper around optL1 of package penalized. Calling peperr, default arguments of optL1 can be changed by passing a named list containing these as argument args.complexity.

Value

Scalar value giving the optimal value for lambda.

See Also

peperr, optL1

peperr documentation built on March 31, 2023, 7:34 p.m.