similar to: Question about .Fortran in glmnet package

Hi, I am trying to do multinomial regression using the glmnet package, but the following gives me an error (for no reason apparent to me): library(glmnet) cv.glmnet(x=matrix(c(1,2,3,4,5,6,1,2,3,4,5,6), nrow=6),y=as.factor(c(1,2,1,2,3,3)),family='multinomial',alpha=0.5, nfolds=2) The error i get is: Error in if (outlist$msg != "Unknown error") return(outlist) : argument is of

Hello R-help list, I have a piece of code written by a grad student here at BU which will segfault when using one data set, but complete just fine using another. Both sets are just text files full of real numbers. It seems like a bug within R. It could be a bug within her data, but again, her data is just a bunch of floats, so her data could be triggering a bug within R. I have tried this

Hello, I got an error message saying Error in lognet(x, is.sparse, ix, jx, y, weights, offset, alpha, nobs, : NA/NaN/Inf in foreign function call (arg 5) when I try to analysis a binary trait using glmnet(R) by running the following code library(glmnet) Xori <- read.table("c:\\SNP.txt", sep='\t'); Yori <- read.table("c:\\Trait.txt", sep=',');

Hi, I created a logistic regression model using the glmnet package. This model is of class "glmnet" or "lognet". I wanted to plot a calibration curve for this model using the calibrate() function from rms package, but the objects used are different, rms requires a fit from lrm(). Is there another function for getting the calibration plot for this glmnet object, or can anyone

Hi, I run R on a server via SSH, over a terminal. After loading a specific package, how do I know what functions are in that package? Is there any way to list or display them? tia. -- View this message in context: http://www.nabble.com/Check-functions-in-package-tp24707084p24707084.html Sent from the R help mailing list archive at Nabble.com.

R gurus, I have a data set that looks something like this: Site Species DBH #Vines G PLOC 45.9 4 G ACNE 23.3 1 G ACNE 12.0 0 G FRAM 35.9 5 G AEGL 11.2 2 N PLOC 77.3 12 N JUNI 78.6 7 N ACNE 18.9 1 N ACNE 15.7 3 N ACRU 35.5 4 H ACSA2 24.1 6 H ULAM 35.2 7 There are 730 individual trees (22 species) from four sites in the actual data set. I would like to create a second data frame that

G'day all, I had a look at the GLM code of R (1.4.1) and I believe that there are problems with the function "glm.fit" that may bite in rare circumstances. Note, I have no data set with which I ran into trouble. This report is solely based on having a look at the code. Below I append a listing of the glm.fit function as produced by my system. I have added line numbers so that I

Hi, I have problem with GPO and dns/kerberos resolution I do a samba -i -d3 to a log file and started on client: gpupdate /force: lpcfg_load: refreshing parameters from /srv/samba/etc/smb.conf params.c:pm_process() - Processing configuration file "/srv/samba/etc/smb.conf" samba version 4.1.0rc2 started. Copyright Andrew Tridgell and the Samba Team 1992-2013 ... ldb_wrap open of

Hi, I was trying to install package glmnet in R, but failed and it show such messages: * Installing *source* package glmnet ... This package has only been tested with gfortran. So some checks are needed. R_HOME is /home/username/R/R-2.9.0 Attempting to determine R_ARCH... R_ARCH is Attempting to detect how R was configured for Fortran 90.... Unsupported Fortran 90 compiler or Fortran 90

Dear All, I want to generate survival curve with cox model but I want to estimate the coefficients using glmnet. However, I also want to include a strata() term in the model. Could anyone please tell me how to have this strata() effect in the model in glmnet? I tried converting a formula with strata() to a design matrix and feeding to glmnet, but glmnet just treats the strata() term with one

Hello, I?m trying to in install the package 'glmnet' but I get always the error massage "package ?Matrix? is not available". I search on you site, but I coundn?t find the package there either. Is their still a package called "Matrix"? Or how can I use "glmnet"? Thank You in advance. Kind regards J.Hemmersbach

Hi there, I am trying to use predict() with an object returned by cv.glmnet(), and get the following error: no applicable method for 'predict' applied to an object of class "cv.glmnet" What's wrong? my code: x=matrix(rnorm(100*20),100,20) y=rnorm(100) cv.fit=cv.glmnet(x,y) predict(cv.fit,newx=x[1:5,]) coef(cv.fit) Thanks so much, Asaf -- View this message in context:

dear all, It appears that glmnet(), when "selecting" the covariates entering the model, skips from K covariates, say, to K+2 or K+3. Thus 2 or 3 variables are "added" at the same time and it is not possible to obtain a ranking of the covariates according to their importance in the model. On the other hand lars() "adds" the covariates one at a time. My question

Hello I'm having trouble using lars and glmnet functions to predict on a new data set with different nrow then the original : for instance: ============= log.1 = glm(temp.data$TL~(.),temp.data,family = binomial,x=TRUE,y=TRUE) nrow(test.data) != nrow(temp.data # == TRUE Val.frame = model.frame(log.1,test.data) # returns a data frame with the variables needed to use log.1

Dear All, Can the x matrix in the glmnet() function of glmnet package be a data.frame with numeric columns and factor columns? I am asking this because I have a model with both numeric and categorical predictors, which I would like to study with glmnet. I have already tried to use a data.frame, but with no success -- as far as I know, the matrix object can only have data of a single type. Is

glmnet is a package that fits the regularization path for linear, two- and multi-class logistic regression models with "elastic net" regularization (tunable mixture of L1 and L2 penalties). glmnet uses pathwise coordinate descent, and is very fast. Some of the features of glmnet: * by default it computes the path at 100 uniformly spaced (on the log scale) values of the

glmnet is a package that fits the regularization path for linear, two- and multi-class logistic regression models with "elastic net" regularization (tunable mixture of L1 and L2 penalties). glmnet uses pathwise coordinate descent, and is very fast. Some of the features of glmnet: * by default it computes the path at 100 uniformly spaced (on the log scale) values of the

Hello fellow R users, I have been getting a strange error message when using the cv.glmnet function in the glmnet package. I am attempting to fit a multinomial regression using the lasso. covars is a matrix with 80 rows and roughly 4000 columns, all the covariates are binary. resp is an eight level factor. I can fit the model with no errors but when I try to cross-validate after about 30 seconds

Dear R users, if all my numerical variables in my datasets having the same units, may I leave them unnormalized, just do cv.glmnet directly(cv.glmnet(data,standardize=FALSE))? i know normally if there is a mixture of numerical and categorical , one has to standardize the numerical part before applying cv.glmnet with standardize=fase, but that's due to the different units in the numerical

Hi, all: Does anybody know how to avoid the intercept term in cv.glmnet coefficient? When I say "avoid", it does not mean using coef()[-1] to omit the printout of intercept, it means no intercept at all when doing the analysis. Thanks. [[alternative HTML version deleted]]