similar to: Lars package

Colleagues: I have encountered the following situation: SERIES OF COMMANDS source("File1") MORE COMMANDS source("File2") Optimally, I would like File1 and File2 to be merged into a single file (FileMerged). However, if I wrote the following: SERIES OF COMMANDS source("FileMerged") MORE COMMANDS I encounter an error: the File2 portion of FileMerged

Hi, Is there any way of telling Asteirsk to withhold answer subversion on a call till I call Answer. My DP looks like this: [incoming] Exten => 18005551212,1,Noop() same => n,Answer same => n,Mset(__uid=${SIPCALLID}) same => n,MixMonitor(/tmp/FROM_CALLER_${uid}-${START}.WAV) same => n,Dial(Local/1 at dial_call_center/n&Local/2 at dial_call_center /n&Local/3 at

On Oct 15, 2009, at 10:45 AM, Chris Lattner wrote: > Unfortunately, we found out at the last minute that Apple has a rule > which prevents its engineers from giving video taped talks or > distributing slides. We will hold onto the video and slide assets in > case this rule changes in the future. > > -Chris Chris, I hope you can pass my message along to the people at Apple

I too am disappointed that not all talk slides are posted. To me it speaks poorly of the whole meeting since there were parallel sessions and not everyone could attend in person all the sessions they wanted to. The slides are, I thought, meant to be like the "proceedings" and If I recall some of the Apple slides are present from previous years but not this year. Vinod On Sat, Oct 17,

Dear R-users, I would like to know what are the commands to install (from a local zip file) a package and then to load it. Thaks all, Bests, Caio "Perco a consciencia, mas n併o importa, encontro a maior serenidade na alucina佺ao. 伾 curioso como n併o sei dizer quem sou. Quer dizer, sei-o bem, mas n併o posso dizer. Sobretudo tenho medo de dizer, porque no momento em que tento falar, n併o

I am trying to investigate the interaction term in the below. The paradigm in aquatic systems is that algal production is either nitrogen (TIN) or Phosphorus limited, and I am trying to investigate this- what is the best way to go about investigating the interaction term. I have some thoughts on the above, but I will withhold them to see what others think. Thanks for your help. d <-

Hi, I am trying to use lars on my data. After getting the model and did the prediction, I compare the predicted value and the coefficients and it seems like there should be a constant term in the model. I have gone through the documentation of the lars package and I can't seem to find how to get this piece of information from the lars object. Can somebody help me? Thanks a lot! Mark

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

hello, I have the following questions with the R package lars(). I would really appreciate som help here. 1. do I have to standardize the predictors and the response? 2. the function cv.lars(): how can I specify it is for lasso not stagewise or lars? your help will be really appreciated. thanks,

Hi! Ok, probably my last mail was too long. Questions are: * Did someone try lars on data with much more components than data points? Did you observe bad overfitting, too? Any other observations? * Why might the lars (least angle regression from lars package) method produce beta values that shoot up into the sky (until they overflow), and why might the Cp values start at a _negative_

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

Hi All, when i run cv.lars(x3,y3) it runs fine. but when i run cv.lars(x3,y3,fraction=seq(0,0.1,100)) I get the following error. Error in apply((y[omit] - fit)^2, 2, mean) : dim(X) must have a positive length Any help/suggestions will be appreciated. Thanks. Harsh --------------------------------- [[alternative HTML version deleted]]

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

Insightful is seeking a pre-doctoral student and an undergraduate student for two internship positions. The primary responsibilities are to assist in the development of software for high-dimensional regression and machine learning applications using least angle regression (LARS). The pre-doctoral candidate should have a background and interest in statistical methodology, algorithms, data

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

I am trying to extract coefficients from lars fit and can't find how to get intercept. E.g. y = rnorm(10) x = matrix(runif(50),nrow=10) X = data.frame(y,x) fit1 = lars(as.matrix(X[,2:6]),as.matrix(X[,1])) fit2 = lm(y~.,data=X) Then, if I do: > predict(fit1,s=1,mode='fraction',type='coefficients')$coef X1 X2 X3 X4 X5 0.3447570

I got my posting bounced and sorry if I accidentally post twice. I have been looking at 'lars' pkg and got puzzled by the behavior of function 'lars'. I want to do weighted lasso regression and can't get a match from lars output with lm output. Here is an example: y = rnorm(10) x = matrix(runif(50),nrow=10) X = data.frame(y,x) z = runif(10) X = data.frame(y,x,z) X$z = X$z /

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

I am trying to use the lars package in R to carry out lasso analysis. However, I am having some problems. Please could you help me with the following questions: 1) Exactly what format do x and y need to be in for cv.lars(x, y) and lars (x, y)? And what information do x and y need to contain exactly? I have tried using to test just a simple matrix of numeric values for x and a simple vector of