similar to: glmnet

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

Hello all, I would like to read the specific line number row of a direct access file (which is stored as a n_row*n_col matrix of elements kind=p) without reading all the preceding lines (i.e 1,2,..,row-1). Is there a function in R that can perform this task? To solve my issue, I tried without to call Fortran from R by doing the following steps: I) I wrote a subroutine in fortran called

Gracias Carlos una vez más, pero no es exactamente lo que quiero Con colMeans estas calculando por columnas, pero yo quiero que calcule asi: mean(datos[1:20,1:20]), pero claro, para toda la secuencia. mean(datos[1:20,1:20]) me devuelve el error-> Error in datos[1:2, 1:2] : object of type 'closure' is not subsettable Date: Tue, 17 Nov 2015 18:34:59 +0100 Subject: Re: [R-es]

Hi, I am attempting to evaluate the prediction error of a coxph model that was built after feature selection with glmnet. In the preprocessing stage I used na.omit (dataset) to remove NAs. I reconstructed all my factor variables into binary variables with dummies (using model.matrix) I then used glmnet lasso to fit a cox model and select the best performing features. Then I fit a coxph model

Hi all, I am using the glmnet R package to run LASSO with binary logistic regression. I have over 290 samples with outcome data (0 for alive, 1 for dead) and over 230 predictor variables. I currently using LASSO to reduce the number of predictor variables. I am using the cv.glmnet function to do 10-fold cross validation on a sequence of lambda values which I let glmnet determine. I then take

¿Qué quieres decir con "valores que quiera"?. ¿Quieres calcular la media de unas regiones de la matriz con algún tipo de patrón? ¿periodicidad? Si es que no, basta como te mostraba en el ejemplo, definir unos índices (tu 1 y 20) y ya está... Saludos, Carlos Ortega www.qualityexcellence.es El 17 de noviembre de 2015, 19:29, Jesús Para Fernández < j.para.fernandez en hotmail.com>

Dear R users: Recently, I learn to use penalized logistic regression. Two packages (penalized and glmnet) have the function of lasso. So I write these code. However, I got different results of coef. Can someone kindly explain. # lasso using penalized library(penalized) pena.fit2<-penalized(HRLNM,penalized=~CN+NoSus,lambda1=1,model="logistic",standardize=TRUE) pena.fit2

Hi Everybody! I must start with a declaration that I am a sparse user of R. I am creating a credit scorecard using a dataset which has a variable depicting actual credit history (good/bad) and 41 other variables of yes/no type. The procedure I am asked to follow is to use a penalized logistic procedure for variable selection. I have located the package "glmnet" which gives the complete

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

Hello list. For some reason, the makers of glmnet do not accept a dataframe as input. They expect the input to be a matrix, where the dummies are already precoded. Now I have created a sample dataset with . 11 factor columns with two levels . 4 factor columns with three levels . 135 continuous columns (from a standard normal) . 100 observations (rows) Say this dataframe is in dfrPredictors. What

Dear List, I'm running simulations using the glmnet package. I need to use an 'automated' method for model selection at each iteration of the simulation. The cv.glmnet function in the same package is handy for that purpose. However, in my simulation I have p >> N, and in some cases the selected model from cv.glmet is essentially shrinking all coefficients to zero. In this case,

Hi all. Sorry for the long email. I have been trying to find someone local to work on this with me, without much luck. I went in to our local stats consulting service here, and the guy there told me that I already know more about model selection than he does. :-< He pointed me towards another professor that can perhaps help, but that prof is busy until mid-June, so I want to get as much

Estimado Jesús Para Fernández El ejemplo que usted presenta es algo básico pero no por ello lejos de carecer importancia, al respecto hay varios autores de paquetes que abordaron ese problema buscando optimizar, facilitar, etc. Lo que usted piensa es correcto, si desea buscar optimizar puede leer algo de plyr, data.table, reshape (este tiene un video explicando casi lo que usted plantea), y

Hello, I'm trying to select features of cetain numbers(like 100 out of 1000) via LASSO, based on multinomial model, however, it seems the glmnet package provides a very sparse estimation of coefficients(most of coefficients are 0), which selects very few number of variables, like only 10, based on my easy dataset. I try to connect the choice of lambda to the selecting

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,

While building/checking a package of mine that depends on glmnet, I got the following message: * checking whether the name space can be loaded with stated dependencies ...Warn ing: running command ''"C:/Users/nisabbe/Documents/R/R-2.13.1/bin/i386/Rterm.exe" R_DEFAULT_PACKAGES=NULL --vanilla --slave -f C:\Users\nisabbe\AppData\Local\Tem p\RtmpZpjj07\Rin121ae93''

Dear all, I've recently had some issues getting my package to successfully "check". This was on R-Forge, so it's not obvious for me to provide SessionInfo or the likes (if necessary, Stefan can chime in?). After some research (mainly by Stefan Theussler, driving force behind R-Forge), this turned out to be the root cause: On R-Forge, the version of R installed was the

La verad es que es un asolución sencilla pero muy eficaz. Ya con esta siguiente duda termino: La matriz de cada csv es de 400x500, es decir, 400 filas y 500 columnas. Si quiero calcular la media de diferentes regiones del csv, por ejemplo la media de las 20 primeras filas y 20 primreas columnas, pero del que tiene los 50.000 registros, tomando el valor 1, como pued hacerlo?? He probado con

I have always assumed that having a package in the 'Depends' field would automatically also?import?the namespace. However, it seems that in R 2.15, dependencies do not become available until the package is actually?attached?to the searchpath. Is this intended behavior? The problem appears as follows: Suppose there is a package 'Child' which?Depends, but does not explicitly

For what it's worth it looks like spm2 is specifically for *spatial* predictive modeling; presumably its version of CV is doing something spatially aware. I agree that glmnet is old and reliable. One might want to use a tidymodels wrapper to create pipelines where you can more easily switch among predictive algorithms (see the `parsnip` package), but otherwise sticking to glmnet