# lasso constraint

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## lasso constraint

 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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## Re: lasso constraint

 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 <[hidden email]> 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. > > ______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.