[R] lasso constraint

[Weidong Gu]

Hi,

your code has errors: apply function only has 1 or 2 as margin.

bound is used as turning parameter for summation of absolute
coefficients. lasso runs on a grid of the turning parameter for
varying strength of shrinkage. so each turning value may yield
different sets of coefficients and values. cross validation is used to
estimate the value of the turning parameter which gives the smallest
errors (mse or deviance) on testing data.

Weidong Gu



On Tue, Mar 27, 2012 at 10:35 AM, yx78 <yangxu78 at gmail.com> wrote:
> In the package lasso2, there is a Prostate Data. To find coefficients in the
> prostate cancer example we could impose L1 constraint on the parameters.
>
> code is:
> data(Prostate)
>  p.mean <- apply(Prostate, 5,mean)
>  pros <- sweep(Prostate, 5, p.mean, "-")
>  p.std <- apply(pros, 5, var)
>  pros <- sweep(pros, 5, sqrt(p.std),"/")
>  pros[, "lpsa"] <- Prostate[, "lpsa"]
> l1ce(lpsa ~  . , pros, bound = 0.44)
>
> I can't figure out what dose 0.44 come from. On the paper it said it was
> from  generalized cross-validation and it is the optimal choice.
>
> paper name: Regression Shrinkage and Selection via the Lasso
>
> author: Robert Tibshirani
>
>
>
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