similar to: LASSO coefficients for a specific s

Hi Bruno, You advised following no need to find the best s value. CV does it for you: cvres<-cv.lars(X,Y,K=10,type='lasso') sAtBest<-cvres$fraction[which.min(cvres$cv)] fits <- predict.lars(object, type="coefficients", s=sAtBest, mode="fraction") in thread https://stat.ethz.ch/pipermail/r-help/2007-June/133982.html My problem is that, cvres$cv is non empty

hello I tried to use lars() but neither with my own data nor with the sample data it works. I get in both cases the following error prompt: > data(diabetes) > par(mfrow=c(2,2)) > attach(diabetes) > x<-lars(x,y) Error in one %*% x : requires numeric matrix/vector arguments > x<-lars(x,y, type="lasso") Error in one %*% x : requires numeric matrix/vector arguments

When plotting a lars object, I cannot find a way to plot solid lines. Even when the arguments breaks=F and lty="solid" are used, the vertical lines at the break points do not plot but asterisks indicating the breaks still plot as part of each path leaving solid lines broken up by asterisks at the break points. I'm using the following code. larsfit <-

Hi, I've noticed that if I disconnect or reconnect a phone from the net, Asterisk take long time to realize that (even more then 10 minutes). Is there a way to reduce this time, working on the configuration files? Thank you. silvia ------------------------------------------------------ Passa a Infostrada. ADSL e Telefono senza limiti e senza canone Telecom http://click.libero.it/infostrada

Dear All, I am using lars package written by Dr. Trevor Hastie, the version is lars_0.9-5 downloaded from cran. When I ran the diabetes example data attached in package, I found that the beta outputs from different machines are different. The difference is only about 10^-11 to 10^-12, some friends suggested that it possibly is a machine precision problem. But I check the machine numerical

First I wanted to thank both Marc Schwartz Greg Snow and for their reply. Then I needed to add a level of complexity to the problem. I would be able to create the biggest possible matrix. In other way does it exist a method to ask smthing like the following : max number of rows for a matrix if column=x? Thank you ------------------------------------------------------ Passa a Infostrada.

Hello, Given a vector I would like to rapidly identify duplicated non contiguous elements. Given for example c(1, 1, 2, 3, 2, 4, 5, 6, 4) I would like to get: FALSE FALSE TRUE FALSE TRUE TRUE FALSE FALSE TRUE In fact I need to check this on the columns of a matrix! I can do that of couse with loops but is there any function already available? Thanks

Dear members, I am wondering if there are any functions to perform the Kernel Fisher Discriminant method, especially for multi-class problems, in R. I would appreciate any kind of information on this. Thanks for your time. Seungho Huh, Ph.D. Research Statistician RTI International North Carolina, USA [[alternative HTML version deleted]]

Dear sir or ma'am, I have a question about the dataset "fgl." The dataset seems to be in the "VR" package, so I tried to download it from CRAN. However, after downloading, when I tried to load the package, it was not in my package list. I am wondering what is wrong. Any advice on how to access the fgl dataset would be appreciated. Thanks. Seungho Huh

I have functions using get.hist.quote() from library tseries. It seems that something changed (yahoo) and function get broken. try with a simple get.hist.quote('IBM') and let me kow if for someone it is still working. I get this error: Error in if (!quiet && dat[n] != start) cat(format(dat[n], "time series starts %Y-%m-%d\n")) : missing value where

Dear R-users I'm trying to use lasso in lars package for subset regression, I have a large matrix of size 1000x100 and my aim is to select a subset k of the 100 variables. Is there any way in lars to fix the number k (i.e. to select the best 10 variables) library(lars) aa=lars(X,Y,type="lasso",max.steps=200) plot(aa,plottype="Cp") aa$RSS which.min(aa$RSS)

Hello everybody I'm very new at using R so probably this is a very stupid question. I have a matrix of "p" columns and I have to calculate for each of them the "two sample t-statistic" and p-value and to save the results into two different vectors. I have divided my matrix into two submatrices: submatrix A containing the first "n1" rows (p columns) and submatrix B

Hi, all, I am using the lars package for lasso estimate. So I get a lasso fit first: lassofit = lars(x,y,type ="lasso",normalize=T, intercept=T) Then I want to get coefficient with respect to a certain value of \lambda (the tuning parameter), I know lars has three mode options c("step", "fraction", "norm"), but can I use the \lambda value instead

Dear useRs (called Frank Harrell, most likely), after having preached for years to my medical colleagues to be cautious with stepwise selection procedures, they chanted back asking for an alternative when using mixed models. There is a half dozen laXXX packages around for all types of linear models, but as far I see there is none for mixed models such as lme. Even boot.stepAIC (which I

Hi all, I have a data set containing variables LOSS, GDP, HPI and UE. (I have attached it in case it is required). Having renamed the variables as l,g,h and u, I wish to run a Lasso Regression with l as the dependent variable and all the other 3 as the independent variables. data=read.table("data.txt", header=T) l=data$LOSS h=data$HPI u=data$UE g=data$GDP matrix=data.frame(l,g,h,u)

Hi, I am trying to do a lasso regression using the lars package with the following data (see attached): FastestTime WinPercentage PlacePercentage ShowPercentage BreakAverage FinishAverage Time7Average Time3Average Finish 116.90 0.14 0.14 0.29 4.43 3.29 117.56 117.77 5.00 116.23 0.29 0.43 0.14 6.14 2.14 116.84 116.80 2.00 116.41 0.00 0.14 0.29 5.71 3.71 117.24

I've got this dataframe X12 X14 X17 X19 vitigni years 1 1 4 78 54 rie 2005 2 1 4 7 4 rie 2005 3 1 4 75 5 rie 2005 4 2 5 66 5 croa 2005 5 1 4 4 46 croa 2005 6 2 5 7 6 croa 2005 7 3 2 56 5 rie 2006 8 3 6 4 7 rie 2006 9 3 2 36 7 rie 2006 10 1 5 3 7 croa 2006 11 1

I'm having the exact problem outlined in a previous post from 2005 - unfortunately the post was never answered: http://tolstoy.newcastle.edu.au/R/help/05/10/15055.html When running: lm2=lars(x2,y,type="lasso",use.Gram=F) I get an error: Error in if (zmin < gamhat) { : missing value where TRUE/FALSE needed ...when running lasso via lars() on a 67x3795 set of predictors. I

Hi! This is my first time posting. I've read the general rules and guidelines, but please bear with me if I make some fatal error in posting. Anyway, I have a continuous response and 29 predictors made up of continuous variables and nominal and ordinal categorical variables. I'd like to do lasso on these, but I get an error. The way I am using "lars" doesn't allow for the

Hi, perhaps you can help me to find out, how to find the best Lambda in a LASSO-model. I have a feature selection problem with 150 proteins potentially predicting Cancer or Noncancer. With a lasso model fit.glm <- glmpath(x=as.matrix(X), y=target, family="binomial") (target is 0, 1 <- Cancer non cancer, X the proteins, numerical in expression), I get following path (PICTURE