lol-package: Lots of Lasso

Description Details Author(s) References See Also Examples

Description

Various optimization methods for Lasso inference with matrix wrapper.

Details

Package: lol
Type: Package
Version: 0.99.0
Date: 2011-04-02
License: GPL-2
LazyLoad: yes

Author(s)

Yinyin Yuan Maintainer: Yinyin Yuan <[email protected]>

References

Goeman, J. J. (2009), L1 penalized estimation in the cox proportional hazards model. Biometrical Journal. N. Meinshausen and P. Buehlmann (2010), Stability Selection (with discussion), Journal of the Royal Statistical Society, Series B, 72, 417-473.

See Also

lasso, matrixLasso

Examples

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data(chin07)
data <- list(y=t(chin07$ge), x=t(chin07$cn))
res <- matrixLasso(data, method='cv', nFold=5)
res

Example output

Loading required package: penalized
Loading required package: survival
Welcome to penalized. For extended examples, see vignette("penalized").
Loading required package: Matrix
 Non-zero coefficients in total: 42
 from a total of 339 predictors
 and 7 responses

lol documentation built on Nov. 1, 2018, 3:28 a.m.