fit.LASSO

response. Could be numeric vector for linear regression, <code>Surv</code> object for Cox regression or a binary vector for logistic regression.

response

<code>n*p</code> matrix of covariates.

LASSO penalty. <code>lambda1</code> of <code>penalized</code> call.

cplx

additional arguments passed to <code>penalized</code> call.

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Interface for fitting survival models with the lasso, conforming to the requirements of argument <code>fit.fun</code> in <code>peperr</code> call.

models

regression

survival

Designed for prediction error estimation
through resampling techniques, possibly accelerated by parallel
execution on a compute cluster. Newly developed model fitting
routines can be easily incorporated. Methods used in the package are detailed in
Porzelius Ch., Binder H. and Schumacher M. (2009) <doi:10.1093/bioinformatics/btp062>
and were used, for instance, in
Porzelius Ch., Schumacher M.and Binder H. (2011) <doi:10.1007/s00180-011-0236-6>.

fit.LASSO: Interface function for fitting a generalised linear model with the lasso

Description

Usage

Arguments

Value

Details

See Also