[R] lasso constraint

[Bert Gunter]

Inline:

On Tue, Mar 27, 2012 at 10:00 AM, Weidong Gu <anopheles123 at gmail.com> wrote:
> Hi,
>
> your code has errors: apply function only has 1 or 2 as margin.

FALSE.  Please re-read the Help files. It works as expected with
arbitrary higher dim arrays.

-- Bert


>
> 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
>>
>>
>>
>> --
>> View this message in context: http://r.789695.n4.nabble.com/lasso-constraint-tp4508998p4508998.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help at r-project.org mailing list
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> and provide commented, minimal, self-contained, reproducible code.



-- 

Bert Gunter
Genentech Nonclinical Biostatistics

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