similar to: qustion with lars (lasso) package

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'm having trouble running 'lars'. When I install it I get the following warning: >install.packages('lars') Warning in install.packages("lars") : argument 'lib' is missing: using 'C:\Users\Anna\Documents/R/win-library/2.10' --- Please select a CRAN mirror for use in this session --- trying URL

Hello, I have a question about the lars package. I am using this package to get the coefficients at a specific LASSO parameter s. data(diabetes) attach(diabetes) object <- lars(x,y,type="lasso") cvres<-cv.lars(x,y,K=10,fraction = seq(from = 0, to = 1, length = 100)) fits <- predict.lars(object, type="coefficients", s=0.1, mode="fraction") Can I assign

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

We have been using Least Angle Regression (lars) to help identify predictors in models where the outcome is continuous. To do so we have been relying on the lars package. Theoretically, it should be possible to use the lars procedure within a general linear model (glm) framework - we are particular interested in a logistic regression model. Does anyone have examples of using lars with logistic

Dear all I am using lars package to do lasso in R. I dont undesrtand what max.steps do?and how I can understand from the outputs to obtain the last steps in this packagethanks for your helpbest [[alternative HTML version deleted]]

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, I am interested in a modification to LARS that allows for positive-only constraints in the variables (with details about how to implement this as described in section 3.4 of the Efron et al (2003) LARS paper). Before I dive into the "lars" package code myself, I was wondering if anyone knew of a version where this is available, or if another package that I have not found can do

Dear all, I met a problem when installing new packages on R, my system is linux fedora 6.0, the following is output. please help me. Thanks. > install.packages('lars') --- Please select a CRAN mirror for use in this session --- Loading Tcl/Tk interface ... done trying URL 'http://www.stathy.com/cran/src/contrib/lars_0.9-5.tar.gz' Content type 'application/x-tar' length

I uploaded a new version of the lars package to CRAN, which incorporates some nontrivial changes. 1) lars now has normalize and intercept options, both defaulted to TRUE, which means the variables are scaled to have unit euclidean norm, and an intercept is included in the model. Either or both can be set to FALSE. 2) lars has an additional type = "stepwise" option; now the list is

I uploaded a new version of the lars package to CRAN, which incorporates some nontrivial changes. 1) lars now has normalize and intercept options, both defaulted to TRUE, which means the variables are scaled to have unit euclidean norm, and an intercept is included in the model. Either or both can be set to FALSE. 2) lars has an additional type = "stepwise" option; now the list is

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 loaded the LARS package,and input: data(diabetes),load the embedded data then I found the varialbes are in this form: x.age,x.bmi......(10 of them),X2.age,X2.bmi....(64 of them) When I input x,R gave me all 10 varialbes,and input X2,it gave me 64 variables,but if I input x.age,it returned nothing,I wonder how to affiliate those subvariable such as x.age,x.bmi to x,since I

Hi, all: I want to call a c program in the windows version R, so I installed ActivePerl and MinGw, wrote the code below in command prompt: Rcmd SHLIB filename.c and I got the error message as follows: Error: c:/R/rw1071/src/gnuwin32/MakeDLL 16: common syntax error. ..... There are errors on line 16 18 20 22 25 28 43 44 45 47 49 50 51 52 53 79 80 81 83. Has any one met the same problem

Hi, Is there an R implementation of least angle regression for binary response modeling? I know that this question has been asked before, and I am also aware of the "lasso2" package, but that only implements an L1 penalty, i.e. the Lasso approach. Madigan and Ridgeway in their discussion of Efron et al (2004) describe a LARS-type algorithm for generalized linear models. Has

Hi, all: I want to call a c program in the windows version R, so I compiled it in VC to get the dll file and use the command ?dyn.load? to call it in R. There is no error appeared for this command, but when I use the command ? is.loaded? to check, it shows that dll file isn?t be loaded. Does anyone have same experience or know the correct way to do it? Best wishes, Guan Xing 5/22/03

Hi useR's, Has anyone used the "Lars" package in R before? If so, is there any tutorial (not manual) or worked out example online for this R package that one can go through to figure out how one can use this package with lasso regression? I appreciate any help I can get in this direction. Sincerely, Vishal -- *Vishal Thapar, Ph.D.* *Scientific informatics Analyst Cold Spring

Hi! When I apply the lars (least-angle-regression) method to my data (3655 features, only 355 data points, no I did not mistype), I observe a strange behaviour: 1) The beta values tend to grow into real high values quite fast up to a point where they overflow and get negative. The overflow is not a problem, I don't need the last part of the analysis anyway, but why do they just

Full_Name: Guan-Hua Huang Version: 2.0.1 OS: Linux Submission from: (NULL) (140.113.114.123) I install the package cluster by using install.packages("cluster"). After install it, it runs fine for function clara, but it does not work for function fanny. I did the following things: library(cluster) set.seed(21) x <- rbind(cbind(rnorm(10, 0, 0.5), rnorm(10, 0, 0.5)),