similar to: Wrapper Subset Selection

R-packages leaps and subselect implement various methods of selecting best or good subsets of predictor variables for linear regression models, but they do not seem to be applicable to logistic regression models. Does anyone know of software for finding good subsets of predictor variables for linear regression models? Thanks. -Ben p.s., The leaps package references "Subset Selection

Hi Pros, I know leaps() computes the best subset selection for linear model, and the bestglm() computes the best subset selection for generalized linear model. Is there any package for best subset selection on random effects model, or mixed effects model? Thank you so much. -- View this message in context:

Hi, I know leaps() computes the best subset selection for linear model, and the bestglm() computes the best subset selection for generalized linear model. Is there any package for best subset selection on random effects model, or mixed effects model? Thank you so much. Tao [[alternative HTML version deleted]]

Hello: Are there any libraries that will do a subset selection for glm's? I looked through leaps, but seems like it is specifically for linear regressions. Thank you. -Dhiren

Hola a todas, Quiero realizar un subset selection usando el paquete leaps, entre mis variables explicativas tengo rezagos de las mismas, por tanto tienen datos NA. sin embargo, al tratar de realizar cross validation me pide que los datos esten en formato data.frame con lo que me arroja un error al ejecutar el algoritmo. Mi pregunta es cómo puedo forzar en un data.frame en que tengo variables

Hello, How would you go about handling the following situation? This is on R 2.12.0 on Ubuntu 32-bit. I have a wrapper function to lm. I want to pass in a subset argument. First, I just thought I'd use "...". ## make example reproducible set.seed(123) df1 <- data.frame(age = rnorm(100, 50, 10), bmi = rnorm(100, 30, sd = 2)) ## create a wrapper using

Dear all , Is there any subset regression (subset selection regression) package in R other than "leaps"? Thanks and regards Alex [[alternative HTML version deleted]]

Hi, I would like to perform a forward selection procedure on a data set with 6 observations and 10 predictors. I tried to run it with regsubsets (I set nvmax=number of observations) but I keep getting these warning messages: Warning messages: 1: 5 linear dependencies found in: leaps.setup(x, y, wt = weights, nbest = nbest, nvmax = nvmax, 2: nvmax reduced to 5 in: leaps.setup(x, y, wt =

Dear R-help - Thanks to those who replied yesterday (Christos H. and Thomas L.) regarding my question on coxph and model formula, the answers worked perfectly. My new question involves the following. I want to run several coxph models (package survival) with the same dataset, but different subsets of that dataset. I have found a way to do this, described below in functions subwrap1 and

Hello, I am wondering if there is a function in R to do all possible subset selection, e.g. using AIC/BIC. It seems to me the function step can not do all possible selection. I am also want to know why the following functions give me different results. It seems I missed some points here. lm <- lm(y ~., data=somedata) AIC(lm) extractAIC(lm) Many thanks, Zheng Huang

hi all is there a package that undertakes subset selection but BASED ON AIC or any other information criteria. i've seen the "subselect" and the "leaps" package but i have not played around with them yet. thanx

Hello List, I was wondering if a package or piece of code exists that will allow all possible subsets regression model selection within program R. I have already looked at step(AIC) which does not test differing combinations of variables within a model as far as I can tell. In addition I tried to use the leaps command, but that does not use the criterion I am looking for. Any help or advice

Dear list, I'm making my current code more generic and would like some advise. The basic problem is subset and the name of the column to be compared for selection. What I've come up with is > data(mammals) > set <- bottompremolars" > subset(mammals, eval(parse(file="",text=set)) > 2) This seems a bit odd. Is there a nicer way? /Fredrik

Hello, I have a question about doing ALL possible subsets regression with a general linear model. My goal is to produce cumulative Akaike weights for each of 7 predictor variables-to obtain this I need R to: 1. Show me ALL possible subsets, not just the best possible subsets 2. Give me an AIC value for each model (instead of a BIC value). I have tried to do this in library(RcmdrPlugin.HH),

My R script needs to pause or wait for a key or mouse on each graph. I used the following statement after each plot par(ask=TRUE) This works on Windows but not on MacOS. Is there any way to pause on graph in MacOS? Thanks, Vu [[alternative HTML version deleted]]

Disclaimer : Short of having local statistical expertise at hand, I'm using this list because I use R for variable selection in the context of linear multiple regression but the questions I have relate more to basic statistics than to R per se. Please redirect me to another appropriate list if such a list exists. I have the very common problem of identifying which (subset of) variables are

A new version (0.7.1) of package 'subselect' has been uploaded to CRAN. Package 'subselect' provides functions which assess the quality of variable subsets as surrogates for a full data set, in an exploratory data analysis, and search for subsets which are optimal under various criteria. As of version 0.7 a new function 'leaps' has been added. 'Leaps' performs a

A new version (0.7.1) of package 'subselect' has been uploaded to CRAN. Package 'subselect' provides functions which assess the quality of variable subsets as surrogates for a full data set, in an exploratory data analysis, and search for subsets which are optimal under various criteria. As of version 0.7 a new function 'leaps' has been added. 'Leaps' performs a

Dear all, I have a small query. Just like we have package leaps which can do variable selection for a linear model, do we have any technique/software for variable selection for panel data? Here are the links to the mentioned packages: https://cran.r-project.org/web/packages/leaps/leaps.pdf https://cran.r-project.org/web/packages/plm/plm.pdf Many thanks, Ashim

Dear R-helpers & bioconductor Sorry for cross-posting, this concerns R-programming stuff applied on Bioconductor context. Also sorry for this long message, I try to be complete in my request. I am trying to write a subset method for a specific class (ExpressionSet from Bioconductor) allowing selection more flexible than "[" method . The schema I am thinking for is the following: