similar to: Strange behaviour of lars method

Hello list, I've been searching around trying to find whether somebody has written such a package of least angle regression on generalized linear models, like what Lasso2 package does. The extension to generalized linear models is briefly discussed in the comment by D. Madigan and G. Ridgeway. Is such a package available? Thanks, Mike [[alternative HTML version deleted]]

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_

Hi! I have the following issues using "R for Mac OS X 2.2.1" (from the ppc-.dmg) on a Mac OS X 10.4.5: 1) The command history is never saved (automatically) to .Rhistory. (The file stays empty.) 2) If I save a history to some file via the "Save History" button, and I load it afterwards via "Load History", only the first entry of the saved History appears in

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

Hi, I changed something in the package "climatol" especially in the function "diagwl". Dos anybody know where I can put the code in the Internet to discuss it? I made from "C" for gradcelsius "?C" with: unit <- list( temp = expression (paste(#"T ", degree,"C")) ) mtext(unit$temp ,2,col=tcol,las=1,line=3,adj=0,at=55)

Hi Folks, I have created a website with over 70 R tutorials on a wide range of subjects. The site is aimed at data analysts who have an idea about what they would like to do, but don't know how to do it in R. The site should be particularly useful for users of statistical packages like SAS, SPSS, Stata, and Systat who would like to get up and running in R quickly. However, I think that it

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

Dear experts, I am asking for help with a question regarding to stratified bootstrap. My dataset is a longitudinal dataset (3 measurements per person at year 1, 4 and 7) composed of multiple clinic centers and multiple participants within each clinic. It has missing values. I want to do a bootstrap to find the standard errors and confidence intervals for my variance components. My model is a

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

There is now a tutorial on bootstrapping and other resampling methods at: http://www.burns-stat.com/pages/Tutor/bootstrap_resampling.html Corrections and other suggestions are welcome. The project started because a novice asked me about bootstrapping. My response was, "How dare you bug me while I'm playing with my cats, just google for it." My correspondent was not very impressed

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

Sometimes one might like to obtain pointwise bootstrap bias-corrected, accelerated (BCA) confidence intervals for a large number of statistics computed from a single dataset. For instance, one might like to get (so as to plot graphically) bootstrap confidence bands for the fitted values in a regression model. (Example: Chiu S et al., Early Acceleration of Head Circumference in Children with

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

Hello, I learnt there's an advanced R/Splus course in Boston this january. Anyone got the announcement? please kindly forward it to me. Best, Eugene

Dear R useres, I'm interested in getting a series of time-varying correlation, simply between two random variables. Could you please introduce a package to do this task? Thank you so much for any help. Amir --------------------------------- Don't pick lemons. [[alternative HTML version deleted]]

Hi, consider this one as an FYI, or a seed for further discussion. I am aware that many traps on sample() have been reported over the years. I know that these are also documents in help("sample"). Still I got bitten by this while writing sample(units, size=length(units)); where 'units' is an index (positive integer) vector. It works in all cases as expected (=I expect)

Hi I was wondering if there is a permutation test available in R for linear models with continuous dependent covariates. I want to do a test like the one shown here. bmi<-rnorm(100,25) x<-c(rep(0,75),rep(1,25)) y<-rnorm(100)+bmi^(1/2)+rnorm(100,2)*x+bmi*x H0<-lm(y~1+x+bmi) H1<-lm(y~1+x+bmi+x*bmi) anova(H0,H1) summary(lm(y~1+x+bmi)) But I want to use permutation testing to

Hello all, I am trying to run a two sample t-test on a matrix which is a 196002*22 matrix. I want to run the t-test, row-wise, with the first 11 columns being a part of the first group and columns 12-22 being a part of the second group. I tried running something like (temp.matrix being my 196002*22 matrix) t.test(temp.matrix[,1:11],temp.matrix[,12:22],paired=TRUE) or somthing like

Hi, I am writing to seek some guidance regarding using Lasso regression with the R package LARS. I have introductory statistics background but I am trying to learn more. Right now I am trying to duplicate the results in a paper for shRNA prediction "An accurate and interpretable model for siRNA efficacy prediction, Jean-Philippe Vert et. al, Bioinformatics" for a Bioinformatics project

I suggest a simple enhancement to segments() and arrows() to facilitate drawing horizontal and vertical segments -- set default values for the second x and y arguments equal to the first set. This is handy, especially when the expressions for coordinates are long. Compare: Segments: < function (x0, y0, x1 = x0, y1 = y0, col = par("fg"), lty = par("lty"), --- > function