similar to: glmnet() vs. lars()

dear all, apologizes for this OT =========================== 28th International Workshop on Statistical Modelling (IWSM), Palermo (Italy) 8-12 July 2013. http://iwsm2013.unipa.it Dear friend, For your information, I would like to bring to your attention that deadline for submission of abstracts is FEBRUARY 18 If you are still interested to visit Palermo (and taste its specialities :-))

dear all, When I use all.vars(), I am interest in extracting only the variable names.. Here a simple example all.vars(as.formula(y~poly(x,k)+z)) returns [1] "y" "x" "k" "z" and I would like to obtain "y" "x" "z" Where is the trick? many thanks vito -- ==================================== Vito M.R. Muggeo Dip.to Sc

dear all, apologizes for this off topic. I would like to inform you that registration and paper submission for the 28th International Workshop on Statistical Modelling (IWSM) to be held in Palermo (Italy) 8-12 July 2013 is now open at http://iwsm2013.unipa.it Register at http://iwsm2013.unipa.it/?cmd=registration and then submit your abstract. Deadlines for Abstract submission is February 4,

dear all, I would like to get the lme call without fitting the relevant model. library(nlme) data(Orthodont) fm1 <- lme(distance ~ age, random=list(Subject=~age),data = Orthodont) To get fm1$call without fitting the model I use call(): my.cc<-call("lme.formula", fixed= distance ~ age, random = list(Subject = ~age)) However the two calls are not the same (apart from the data

dear all, This is a probably a silly question. If I type > grep("x",c("a.x" ,"b.x","a.xx"),value=TRUE) [1] "a.x" "b.x" "a.xx" Instead, I would like to obtain only "a.x" "b.x" How is it possible to get this result with grep()? many thanks for your attention, best, vito --

dear all, Is the following intentional? Am I missing anything in documentation? d<-data.frame(y=rnorm(10,5,.5),exp=rnorm(10), age=rnorm(10)) formula(lm(exp(y)~exp+age, data=d)) #--> exp(y) ~ exp + age formula(lm(exp(y)~., data=d)) #--> exp(y) ~ age variable 'exp' (maybe indicating "experience") is not included in the model. The same happens with 'log' (and

dear all, I do not if it is a nonsense question.. Is it possible in the R session to get the name of the current .Rdata file that I ran? I mean: suppose I double click the file myfile.Rdata. ls() returns the names of the objects in the current workspace (that is saved in myfile.Rdata). In the current R session, I would like to obtain "myfile.Rdata". Is it possible? Thanks in

Hi, I am trying to do logistic regression for data of 104 patients, which have one outcome (yes or no) and 15 variables (9 categorical factors [yes or no] and 6 continuous variables). Number of yes outcome is 25. Twenty-five events and 15 variables mean events per variable is much less than 10. Therefore, I tried to analyze the data with penalized regression method. I would like please some of the

dear all, I am stuck on the following problem. Give a string like ss1<- "z:f(5, a=3, b=4, c='1:4', d=2)" or ss2<- "f(5, a=3, b=4, c=\"1:4\", d=2)*z" I would like to remove all entries within parentheses.. Namely, I aim to obtain respectively "z:f()" or "f()*z" I played with sub() and gsub() but without success.. Thank you very

dear all, Could anyone explain me the behaviour of median() within by()? (I am running R.2.7.0) thanks, vito > H<-cbind(rep(0:1,l=20),matrix(rnorm(20*2),20,2)) > by(H[,-1],H[,1],mean) INDICES: 0 V1 V2 -0.2101069 0.2954377 --------------------------------------------------------------------------------------------------------------------- INDICES: 1 V1

Could any one help ? I start to learn the glmnet package. I tried with the example in the manual. x=matrix(rnorm(100*20),100,20) y=rnorm(100) fit1=glmnet(x,y) When I tried to fit the model, I received the error message: Error in validObject(.Object) : invalid class "dgCMatrix" object: row indices are not sorted within columns Thank you very much!

Dear all, It appears that MASS::polr() and Design::lrm() return the same point estimates but different st.errs when fitting proportional odds models, grade<-c(4,4,2,4,3,2,3,1,3,3,2,2,3,3,2,4,2,4,5,2,1,4,1,2,5,3,4,2,2,1) score<-c(525,533,545,582,581,576,572,609,559,543,576,525,574,582,574,471,595, 557,557,584,599,517,649,584,463,591,488,563,553,549) library(MASS) library(Design)

Hello list. I was trying to see some of the code for plot.glmnet in package glmnet (this function name is in the documentation). After loading the library, I tried the obvious typing in the name, but I received a message telling me it could not be found. So I fiddled around a little, and noticed that R does not recognize ''plot'' as a generic function, and as such,

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 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:

Hi, is there any chance to install glmnet with gcc-4.5.2? For me it fails on all systems with: trying URL 'http://mirrors.softliste.de/cran/src/contrib/glmnet_1.7.tar.gz' Content type 'application/x-gzip' length 522888 bytes (510 Kb) opened URL ================================================== downloaded 510 Kb * installing *source* package ?glmnet? ... This package has only

Dear list, I would like to know: 1. After I have used the R code (http://pscl.stanford.edu/zeroinfl.r) to fit a zero-inflated negative binomial model, what criteria I should follow to compare and select the best model (models with different predictors)? 2. How can I compare the model I get from question 1 (zero-inflated negative binomial) to other models like glm family models or a logistic

Dear all, This is off-topic, however I hope someone can give me useful suggestion.. Given the regression model y = b0 + b1*x + e I am interested in testing for positive coeffs, namely H0: b0>0 AND b1>0 H1: b0,b1 unconstrained It is simple to estimate the model under H0 and H1 (there are several suggestions on the Rlist about estimation but nothing about testing..) perform a likelihood

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

Hello all, I am having trouble with the glmnet package. I used it for the first time last week, after updating R to the current version (2.10.1, running in Windows XP). It seemed to be working fine as I explored what it could do with one of my datasets. A day or two later, using the exact same dataset, it suddenly stopped working. I get the following error every time I try to use glmnet with